From f7f499eb173cd9820cf3b054d06d6472ad5e115b Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Thu, 20 Jun 2024 10:47:55 +0800
Subject: [PATCH 01/35] fixed the potentially wrong namedtuple definitions in
 the svd backend functions, update the docstring of ivy.svd to mention the
 change of content of return when compute_uv is False, update svd's torch
 backend to only compute the necessary second component to be more efficient
 and the relevant docstring in ivy.svd as well

---
 ivy/functional/backends/jax/linear_algebra.py        | 2 +-
 ivy/functional/backends/numpy/linear_algebra.py      | 2 +-
 ivy/functional/backends/paddle/linear_algebra.py     | 2 +-
 ivy/functional/backends/tensorflow/linear_algebra.py | 3 +--
 ivy/functional/backends/torch/linear_algebra.py      | 9 +++------
 ivy/functional/ivy/linear_algebra.py                 | 5 +----
 6 files changed, 8 insertions(+), 15 deletions(-)

diff --git a/ivy/functional/backends/jax/linear_algebra.py b/ivy/functional/backends/jax/linear_algebra.py
index d7b5c55cc9d9a..281ad7eb30315 100644
--- a/ivy/functional/backends/jax/linear_algebra.py
+++ b/ivy/functional/backends/jax/linear_algebra.py
@@ -361,7 +361,7 @@ def svd(
     x: JaxArray, /, *, compute_uv: bool = True, full_matrices: bool = True
 ) -> Union[JaxArray, Tuple[JaxArray, ...]]:
     if compute_uv:
-        results = namedtuple("svd", "U S Vh")
+        results = namedtuple("svd", ['U', 'S', 'Vh'])
         U, D, VT = jnp.linalg.svd(x, full_matrices=full_matrices, compute_uv=compute_uv)
         return results(U, D, VT)
     else:
diff --git a/ivy/functional/backends/numpy/linear_algebra.py b/ivy/functional/backends/numpy/linear_algebra.py
index 20424a1da7ec5..50691e06cfac4 100644
--- a/ivy/functional/backends/numpy/linear_algebra.py
+++ b/ivy/functional/backends/numpy/linear_algebra.py
@@ -291,7 +291,7 @@ def svd(
     x: np.ndarray, /, *, compute_uv: bool = True, full_matrices: bool = True
 ) -> Union[np.ndarray, Tuple[np.ndarray, ...]]:
     if compute_uv:
-        results = namedtuple("svd", "U S Vh")
+        results = namedtuple("svd", ['U', 'S', 'Vh'])
         U, D, VT = np.linalg.svd(x, full_matrices=full_matrices, compute_uv=compute_uv)
         return results(U, D, VT)
     else:
diff --git a/ivy/functional/backends/paddle/linear_algebra.py b/ivy/functional/backends/paddle/linear_algebra.py
index 1a037d570f32a..16cdce79c1a0b 100644
--- a/ivy/functional/backends/paddle/linear_algebra.py
+++ b/ivy/functional/backends/paddle/linear_algebra.py
@@ -521,7 +521,7 @@ def svd(
 ) -> Union[paddle.Tensor, Tuple[paddle.Tensor, ...]]:
     ret = paddle.linalg.svd(x, full_matrices=full_matrices)
     if compute_uv:
-        results = namedtuple("svd", "U S Vh")
+        results = namedtuple("svd", ['U', 'S', 'Vh'])
         return results(*ret)
     else:
         results = namedtuple("svd", "S")
diff --git a/ivy/functional/backends/tensorflow/linear_algebra.py b/ivy/functional/backends/tensorflow/linear_algebra.py
index ca8c412a1149b..39ff8647f1d8f 100644
--- a/ivy/functional/backends/tensorflow/linear_algebra.py
+++ b/ivy/functional/backends/tensorflow/linear_algebra.py
@@ -545,8 +545,7 @@ def svd(
     compute_uv: bool = True,
 ) -> Union[Union[tf.Tensor, tf.Variable], Tuple[Union[tf.Tensor, tf.Variable], ...]]:
     if compute_uv:
-        results = namedtuple("svd", "U S Vh")
-
+        results = namedtuple("svd", ['U', 'S', 'Vh'])
         batch_shape = tf.shape(x)[:-2]
         num_batch_dims = len(batch_shape)
         transpose_dims = list(range(num_batch_dims)) + [
diff --git a/ivy/functional/backends/torch/linear_algebra.py b/ivy/functional/backends/torch/linear_algebra.py
index e8d960d313b37..752d7b42c0959 100644
--- a/ivy/functional/backends/torch/linear_algebra.py
+++ b/ivy/functional/backends/torch/linear_algebra.py
@@ -414,16 +414,13 @@ def svd(
     x: torch.Tensor, /, *, full_matrices: bool = True, compute_uv: bool = True
 ) -> Union[torch.Tensor, Tuple[torch.Tensor, ...]]:
     if compute_uv:
-        results = namedtuple("svd", "U S Vh")
-
+        results = namedtuple("svd", ['U', 'S', 'Vh'])
         U, D, VT = torch.linalg.svd(x, full_matrices=full_matrices)
         return results(U, D, VT)
     else:
         results = namedtuple("svd", "S")
-        svd = torch.linalg.svd(x, full_matrices=full_matrices)
-        # torch.linalg.svd returns a tuple with U, S, and Vh
-        D = svd[1]
-        return results(D)
+        s = torch.linalg.svdvals(x)
+        return results(s)
 
 
 @with_unsupported_dtypes({"2.2 and below": ("float16", "bfloat16")}, backend_version)
diff --git a/ivy/functional/ivy/linear_algebra.py b/ivy/functional/ivy/linear_algebra.py
index 4c61f9fdbbaa0..1c9febe327ad5 100644
--- a/ivy/functional/ivy/linear_algebra.py
+++ b/ivy/functional/ivy/linear_algebra.py
@@ -2130,15 +2130,12 @@ def svd(
         If ``True`` then left and right singular vectors will be computed and returned
         in ``U`` and ``Vh``, respectively. Otherwise, only the singular values will be
         computed, which can be significantly faster.
-    .. note::
-        with backend set as torch, svd with still compute left and right singular
-        vectors irrespective of the value of compute_uv, however Ivy will still
-        only return the singular values.
 
     Returns
     -------
     .. note::
         once complex numbers are supported, each square matrix must be Hermitian.
+        In addition, the return will be a namedtuple ``(S)`` when compute_uv is ``False``
 
     ret
         a namedtuple ``(U, S, Vh)`` whose

From 3db7f17dfb0ca3c33bae9b982ee150af56f93bbb Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Thu, 20 Jun 2024 10:53:58 +0800
Subject: [PATCH 02/35] try to fix the blas_and_lapack_ops.py.svd with correct
 output namedtuple definition and behavior when compute_uv is false

---
 .../frontends/torch/blas_and_lapack_ops.py         | 14 ++++++++++----
 ivy/functional/frontends/torch/linalg.py           |  7 +++++--
 2 files changed, 15 insertions(+), 6 deletions(-)

diff --git a/ivy/functional/frontends/torch/blas_and_lapack_ops.py b/ivy/functional/frontends/torch/blas_and_lapack_ops.py
index a1c8cd9bbe77b..c114b67e293ce 100644
--- a/ivy/functional/frontends/torch/blas_and_lapack_ops.py
+++ b/ivy/functional/frontends/torch/blas_and_lapack_ops.py
@@ -2,6 +2,7 @@
 import ivy
 from ivy.func_wrapper import with_unsupported_dtypes
 import ivy.functional.frontends.torch as torch_frontend
+from collections import namedtuple
 from ivy.functional.frontends.torch.func_wrapper import to_ivy_arrays_and_back
 
 
@@ -191,11 +192,16 @@ def slogdet(A, *, out=None):
 
 @to_ivy_arrays_and_back
 def svd(input, some=True, compute_uv=True, *, out=None):
-    # TODO: add compute_uv
-    if some:
-        ret = ivy.svd(input, full_matrices=False)
+    # TODO: add handling for driver
+    ret = ivy.svd(input, full_matrices=not some, compute_uv=compute_uv)
+    results = namedtuple("svd", ['U', 'S', 'V'])
+    if compute_uv:
+        ret = results(ret.U, ret.S, ret.Vh.mH)
     else:
-        ret = ivy.svd(input, full_matrices=True)
+        shape = input.shape
+        m = shape[-2]
+        n = shape[-1]
+        ret = results(ivy.zeros((m,m)), ret.S, ivy.zeros((n,n))) # TODO: keep the zeros on same device as input
     if ivy.exists(out):
         return ivy.inplace_update(out, ret)
     return ret
diff --git a/ivy/functional/frontends/torch/linalg.py b/ivy/functional/frontends/torch/linalg.py
index 3df44b0ae3fa7..7b6ae985ee102 100644
--- a/ivy/functional/frontends/torch/linalg.py
+++ b/ivy/functional/frontends/torch/linalg.py
@@ -326,8 +326,11 @@ def solve_ex(A, B, *, left=True, check_errors=False, out=None):
     {"2.2 and below": ("float32", "float64", "complex32", "complex64")}, "torch"
 )
 def svd(A, /, *, full_matrices=True, driver=None, out=None):
-    # TODO: add handling for driver and out
-    return ivy.svd(A, compute_uv=True, full_matrices=full_matrices)
+    # TODO: add handling for driver
+    ret = ivy.svd(A, compute_uv=True, full_matrices=full_matrices)
+    if ivy.exists(out):
+        return ivy.inplace_update(out, ret)
+    return ret
 
 
 @to_ivy_arrays_and_back

From 46d180a07670a3edc21e280efef55a1e582efcf2 Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Thu, 20 Jun 2024 15:09:18 +0800
Subject: [PATCH 03/35] try to fix the blas_and_lapack_ops.py.svd with correct
 output namedtuple definition and behavior when compute_uv is false

---
 ivy/functional/frontends/torch/blas_and_lapack_ops.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ivy/functional/frontends/torch/blas_and_lapack_ops.py b/ivy/functional/frontends/torch/blas_and_lapack_ops.py
index c114b67e293ce..074a1a62a75a5 100644
--- a/ivy/functional/frontends/torch/blas_and_lapack_ops.py
+++ b/ivy/functional/frontends/torch/blas_and_lapack_ops.py
@@ -201,7 +201,7 @@ def svd(input, some=True, compute_uv=True, *, out=None):
         shape = input.shape
         m = shape[-2]
         n = shape[-1]
-        ret = results(ivy.zeros((m,m)), ret.S, ivy.zeros((n,n))) # TODO: keep the zeros on same device as input
+        ret = results(ivy.zeros((m,m), device=input.device), ret.S, ivy.zeros((n,n), device=input.device))
     if ivy.exists(out):
         return ivy.inplace_update(out, ret)
     return ret

From dce10a65abb1d694fb051d12057af2a3183aff33 Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Sun, 30 Jun 2024 18:46:34 +0800
Subject: [PATCH 04/35] replace the unimplemented tensor.mH used to the
 implemented adjoint, fixed the wrong shape and dtype of return. Now there are
 somehow numerial difference between return of groundtruth torch.svd and
 ivy.svd

---
 .../frontends/torch/blas_and_lapack_ops.py         | 14 ++++++++------
 1 file changed, 8 insertions(+), 6 deletions(-)

diff --git a/ivy/functional/frontends/torch/blas_and_lapack_ops.py b/ivy/functional/frontends/torch/blas_and_lapack_ops.py
index 074a1a62a75a5..7100d79330090 100644
--- a/ivy/functional/frontends/torch/blas_and_lapack_ops.py
+++ b/ivy/functional/frontends/torch/blas_and_lapack_ops.py
@@ -193,15 +193,17 @@ def slogdet(A, *, out=None):
 @to_ivy_arrays_and_back
 def svd(input, some=True, compute_uv=True, *, out=None):
     # TODO: add handling for driver
-    ret = ivy.svd(input, full_matrices=not some, compute_uv=compute_uv)
+    retu = ivy.svd(input, full_matrices=not some, compute_uv=compute_uv)
     results = namedtuple("svd", ['U', 'S', 'V'])
     if compute_uv:
-        ret = results(ret.U, ret.S, ret.Vh.mH)
+        ret = results(retu[0], retu[1], ivy.adjoint(retu[2]))
     else:
-        shape = input.shape
-        m = shape[-2]
-        n = shape[-1]
-        ret = results(ivy.zeros((m,m), device=input.device), ret.S, ivy.zeros((n,n), device=input.device))
+        shape = list(input.shape)
+        shape1 = shape
+        shape2 = shape
+        shape1[-2] = shape[-1]
+        shape2[-1] = shape[-2]
+        ret = results(ivy.zeros(shape1, device=input.device, dtype=input.dtype), retu[0], ivy.zeros(shape2, device=input.device, dtype=input.dtype))
     if ivy.exists(out):
         return ivy.inplace_update(out, ret)
     return ret

From 0c13ce6d1d8f1282022c0d777ef59ec486246962 Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Wed, 3 Jul 2024 13:49:51 +0800
Subject: [PATCH 05/35] update test of torch.blas_and_lapack_ops.svd to
 calculate the validity of result instead of matching values

---
 .../frontends/torch/blas_and_lapack_ops.py    |  1 -
 .../test_torch/test_blas_and_lapack_ops.py    | 70 ++++++++++++++-----
 2 files changed, 51 insertions(+), 20 deletions(-)

diff --git a/ivy/functional/frontends/torch/blas_and_lapack_ops.py b/ivy/functional/frontends/torch/blas_and_lapack_ops.py
index 7100d79330090..72fc1c415b899 100644
--- a/ivy/functional/frontends/torch/blas_and_lapack_ops.py
+++ b/ivy/functional/frontends/torch/blas_and_lapack_ops.py
@@ -192,7 +192,6 @@ def slogdet(A, *, out=None):
 
 @to_ivy_arrays_and_back
 def svd(input, some=True, compute_uv=True, *, out=None):
-    # TODO: add handling for driver
     retu = ivy.svd(input, full_matrices=not some, compute_uv=compute_uv)
     results = namedtuple("svd", ['U', 'S', 'V'])
     if compute_uv:
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
index f66853869c8e4..daa6b8cbbd592 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
@@ -848,11 +848,10 @@ def test_torch_qr(
 @handle_frontend_test(
     fn_tree="torch.svd",
     dtype_and_x=helpers.dtype_and_values(
-        available_dtypes=helpers.get_dtypes("float", index=1),
-        min_num_dims=3,
-        max_num_dims=5,
-        min_dim_size=2,
-        max_dim_size=5,
+        available_dtypes=helpers.get_dtypes("float"),
+        min_value=0,
+        max_value=10,
+        shape=helpers.ints(min_value=2, max_value=5).map(lambda x: (x, x)),
     ),
     some=st.booleans(),
     compute=st.booleans(),
@@ -860,25 +859,58 @@ def test_torch_qr(
 def test_torch_svd(
     dtype_and_x,
     some,
-    compute,
-    on_device,
-    fn_tree,
+    compute_uv,
     frontend,
-    test_flags,
     backend_fw,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    on_device,
 ):
-    dtype, x = dtype_and_x
-    helpers.test_frontend_function(
-        input_dtypes=dtype,
-        backend_to_test=backend_fw,
+    input_dtype, x = dtype_and_x
+    x = np.asarray(x[0], dtype=input_dtype[0])
+
+    ret, frontend_ret = helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        init_all_as_kwargs_np={
+            "data": x,
+        },
+        method_input_dtypes=input_dtype,
+        method_all_as_kwargs_np={
+            "some": some,
+            "compute_uv": compute_uv,
+        },
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
         frontend=frontend,
-        test_flags=test_flags,
-        fn_tree=fn_tree,
+        backend_to_test=backend_fw,
         on_device=on_device,
-        input=x[0],
-        some=some,
-        compute_uv=compute,
-    )
+        test_values=False,
+    )
+    with helpers.update_backend(backend_fw) as ivy_backend:
+        ret = [ivy_backend.to_numpy(x) for x in ret]
+    frontend_ret = [np.asarray(x) for x in frontend_ret]
+
+    u, s, v = ret
+    frontend_u, frontend_s, frontend_v = frontend_ret
+
+    if compute_uv:
+        helpers.assert_all_close(
+            ret_np=frontend_u @ np.diag(frontend_s) @ frontend_v.T,
+            ret_from_gt_np=u @ np.diag(s) @ v.T,
+            atol=1e-04,
+            backend=backend_fw,
+            ground_truth_backend=frontend,
+        )
+    else:
+        helpers.assert_all_close(
+            ret_np=frontend_s,
+            ret_from_gt_np=s,
+            atol=1e-04,
+            backend=backend_fw,
+            ground_truth_backend=frontend,
+        )
 
 
 @handle_frontend_test(

From 4d0851d1da638ef08db97b52e40ded7795ce31e7 Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Wed, 3 Jul 2024 14:08:36 +0800
Subject: [PATCH 06/35] small fix

---
 .../test_torch/test_blas_and_lapack_ops.py    | 35 ++++++++-----------
 1 file changed, 14 insertions(+), 21 deletions(-)

diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
index daa6b8cbbd592..9baac0f92469d 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
@@ -4,6 +4,7 @@
 from hypothesis import strategies as st, assume
 
 # local
+import ivy
 import ivy_tests.test_ivy.helpers as helpers
 from ivy_tests.test_ivy.helpers import handle_frontend_test
 from ivy_tests.test_ivy.helpers.hypothesis_helpers.general_helpers import (
@@ -854,42 +855,34 @@ def test_torch_qr(
         shape=helpers.ints(min_value=2, max_value=5).map(lambda x: (x, x)),
     ),
     some=st.booleans(),
-    compute=st.booleans(),
+    compute_uv=st.booleans(),
 )
 def test_torch_svd(
     dtype_and_x,
     some,
     compute_uv,
     frontend,
+    test_flags,
+    fn_tree,
     backend_fw,
-    frontend_method_data,
-    init_flags,
-    method_flags,
     on_device,
 ):
     input_dtype, x = dtype_and_x
     x = np.asarray(x[0], dtype=input_dtype[0])
-
-    ret, frontend_ret = helpers.test_frontend_method(
-        init_input_dtypes=input_dtype,
-        init_all_as_kwargs_np={
-            "data": x,
-        },
-        method_input_dtypes=input_dtype,
-        method_all_as_kwargs_np={
-            "some": some,
-            "compute_uv": compute_uv,
-        },
-        frontend_method_data=frontend_method_data,
-        init_flags=init_flags,
-        method_flags=method_flags,
-        frontend=frontend,
+    # make symmetric positive definite beforehand
+    x = np.matmul(x.T, x) + np.identity(x.shape[0]) * 1e-3
+    ret, frontend_ret = helpers.test_frontend_function(
+        input_dtypes=input_dtype,
         backend_to_test=backend_fw,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
         on_device=on_device,
         test_values=False,
+        some=some,
+        compute_uv=compute_uv,
     )
-    with helpers.update_backend(backend_fw) as ivy_backend:
-        ret = [ivy_backend.to_numpy(x) for x in ret]
+    ret = [ivy.to_numpy(x) for x in ret]
     frontend_ret = [np.asarray(x) for x in frontend_ret]
 
     u, s, v = ret

From 3b3670fb14a37d7dc009b05b210213f778726e91 Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Wed, 3 Jul 2024 15:31:01 +0800
Subject: [PATCH 07/35] small fix

---
 .../test_frontends/test_torch/test_blas_and_lapack_ops.py        | 1 +
 1 file changed, 1 insertion(+)

diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
index 9baac0f92469d..d86a0cc937d64 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
@@ -879,6 +879,7 @@ def test_torch_svd(
         fn_tree=fn_tree,
         on_device=on_device,
         test_values=False,
+        input = x,
         some=some,
         compute_uv=compute_uv,
     )

From 71fed6bd9ab0c5ef7d8fcc4a193cdc9016e5ff2c Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Wed, 3 Jul 2024 16:27:00 +0800
Subject: [PATCH 08/35] updated the test for torch.linalg.svd

---
 .../test_frontends/test_torch/test_linalg.py  | 37 +++++++++++++------
 1 file changed, 25 insertions(+), 12 deletions(-)

diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
index 3fe907273c191..7fae4e9765fda 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
@@ -1247,7 +1247,15 @@ def test_torch_solve_ex(
 # svd
 @handle_frontend_test(
     fn_tree="torch.linalg.svd",
-    dtype_and_x=_get_dtype_and_matrix(square=True),
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+        min_value=0,
+        max_value=10,
+        min_num_dims=2,
+        max_num_dims=5,
+        min_dim_size=1,
+        max_dim_size=5,
+    ),
     full_matrices=st.booleans(),
 )
 def test_torch_svd(
@@ -1272,25 +1280,30 @@ def test_torch_svd(
         fn_tree=fn_tree,
         on_device=on_device,
         test_values=False,
-        atol=1e-03,
-        rtol=1e-05,
         A=x,
         full_matrices=full_matrices,
     )
     ret = [ivy.to_numpy(x) for x in ret]
     frontend_ret = [np.asarray(x) for x in frontend_ret]
-
     u, s, vh = ret
     frontend_u, frontend_s, frontend_vh = frontend_ret
+    if full_matrices:
+        helpers.assert_all_close(
+            ret_np=frontend_u[...,:frontend_s.shape[0]] @ np.diag(frontend_s) @ frontend_vh.T,
+            ret_from_gt_np=u[...,:s.shape[0]] @ np.diag(s) @ vh.T,
+            atol=1e-04,
+            backend=backend_fw,
+            ground_truth_backend=frontend,
+        )
+    else:
+        helpers.assert_all_close(
+            ret_np=frontend_u @ np.diag(frontend_s) @ frontend_vh.T,
+            ret_from_gt_np=u @ np.diag(s) @ vh.T,
+            atol=1e-04,
+            backend=backend_fw,
+            ground_truth_backend=frontend,
+        )
 
-    assert_all_close(
-        ret_np=u @ np.diag(s) @ vh,
-        ret_from_gt_np=frontend_u @ np.diag(frontend_s) @ frontend_vh,
-        rtol=1e-2,
-        atol=1e-2,
-        ground_truth_backend=frontend,
-        backend=backend_fw,
-    )
 
 
 # svdvals

From 3fdf4dda9886624fd355bd6086adf5b8f29d728a Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Wed, 3 Jul 2024 18:14:34 +0800
Subject: [PATCH 09/35] find that jax.lax.linalg.svd has a argument
 "subset_by_index" missing

---
 ivy/functional/frontends/jax/lax/linalg.py        | 10 +++++++---
 .../test_jax/test_lax/test_linalg.py              | 15 ++++++++-------
 .../test_torch/test_blas_and_lapack_ops.py        |  5 +++--
 3 files changed, 18 insertions(+), 12 deletions(-)

diff --git a/ivy/functional/frontends/jax/lax/linalg.py b/ivy/functional/frontends/jax/lax/linalg.py
index a48964c859054..d48cac8a85911 100644
--- a/ivy/functional/frontends/jax/lax/linalg.py
+++ b/ivy/functional/frontends/jax/lax/linalg.py
@@ -44,7 +44,11 @@ def qr(x, /, *, full_matrices=False):
 
 
 @to_ivy_arrays_and_back
-def svd(x, /, *, full_matrices=True, compute_uv=True):
-    if not compute_uv:
+@with_unsupported_dtypes({"0.4.14 and below": ("bfloat16",)}, "jax")
+def svd(x, /, *, full_matrices=True, compute_uv=True, subset_by_index=None):
+    #TODO: handle subset_by_index
+    if compute_uv:
+        return tuple(ivy.svd(x, full_matrices=full_matrices))
+    else:
         return ivy.svdvals(x)
-    return ivy.svd(x, full_matrices=full_matrices)
+
diff --git a/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
index 789512cb08421..74501eca12a5f 100644
--- a/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
@@ -161,19 +161,18 @@ def test_jax_qr(
 # svd
 @handle_frontend_test(
     fn_tree="jax.lax.linalg.svd",
-    dtype_and_x=helpers.dtype_and_values(
+    dtype_x=helpers.dtype_and_values(
         available_dtypes=helpers.get_dtypes("float"),
         min_value=0,
         max_value=10,
-        shape=helpers.ints(min_value=2, max_value=5).map(lambda x: (x, x)),
-    ).filter(
-        lambda x: "float16" not in x[0]
-        and "bfloat16" not in x[0]
-        and np.linalg.cond(x[1][0]) < 1 / sys.float_info.epsilon
-        and np.linalg.det(np.asarray(x[1][0])) != 0
+        min_num_dims=2,
+        max_num_dims=5,
     ),
     full_matrices=st.booleans(),
     compute_uv=st.booleans(),
+    index=st.one_of(
+        st.none(), st.tuples(st.integers(min_value=0, max_value=3), st.integers(min_value=3, max_value=5))
+    ),
     test_with_out=st.just(False),
 )
 def test_jax_svd(
@@ -181,6 +180,7 @@ def test_jax_svd(
     dtype_and_x,
     full_matrices,
     compute_uv,
+    index,
     on_device,
     fn_tree,
     frontend,
@@ -203,6 +203,7 @@ def test_jax_svd(
         x=x,
         full_matrices=full_matrices,
         compute_uv=compute_uv,
+        subset_by_index=index,
     )
 
     if compute_uv:
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
index d86a0cc937d64..68493f0e4e19e 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
@@ -852,7 +852,8 @@ def test_torch_qr(
         available_dtypes=helpers.get_dtypes("float"),
         min_value=0,
         max_value=10,
-        shape=helpers.ints(min_value=2, max_value=5).map(lambda x: (x, x)),
+        min_num_dims = 2,
+        max_num_dims = 5,
     ),
     some=st.booleans(),
     compute_uv=st.booleans(),
@@ -883,7 +884,7 @@ def test_torch_svd(
         some=some,
         compute_uv=compute_uv,
     )
-    ret = [ivy.to_numpy(x) for x in ret]
+    ret = [np.asarray(x) for x in ret]
     frontend_ret = [np.asarray(x) for x in frontend_ret]
 
     u, s, v = ret

From c5b59045351f645c1e9d50ed16d2f4564fe8fd28 Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Wed, 3 Jul 2024 22:14:48 +0800
Subject: [PATCH 10/35] fixed the skipping torch svd tests according to
 suggestion, no longer skipping

---
 .../frontends/torch/blas_and_lapack_ops.py           |  2 +-
 .../test_torch/test_blas_and_lapack_ops.py           | 12 ++++++------
 .../test_frontends/test_torch/test_linalg.py         | 12 ++++++------
 3 files changed, 13 insertions(+), 13 deletions(-)

diff --git a/ivy/functional/frontends/torch/blas_and_lapack_ops.py b/ivy/functional/frontends/torch/blas_and_lapack_ops.py
index 72fc1c415b899..47249630a8c58 100644
--- a/ivy/functional/frontends/torch/blas_and_lapack_ops.py
+++ b/ivy/functional/frontends/torch/blas_and_lapack_ops.py
@@ -202,7 +202,7 @@ def svd(input, some=True, compute_uv=True, *, out=None):
         shape2 = shape
         shape1[-2] = shape[-1]
         shape2[-1] = shape[-2]
-        ret = results(ivy.zeros(shape1, device=input.device, dtype=input.dtype), retu[0], ivy.zeros(shape2, device=input.device, dtype=input.dtype))
+        ret = results(ivy.zeros(shape1, device=input.device, dtype=input.dtype), ivy.astype(retu[0], input.dtype), ivy.zeros(shape2, device=input.device, dtype=input.dtype))
     if ivy.exists(out):
         return ivy.inplace_update(out, ret)
     return ret
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
index 68493f0e4e19e..fa75313a9d24d 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
@@ -870,7 +870,7 @@ def test_torch_svd(
 ):
     input_dtype, x = dtype_and_x
     x = np.asarray(x[0], dtype=input_dtype[0])
-    # make symmetric positive definite beforehand
+    # make symmetric positive definite
     x = np.matmul(x.T, x) + np.identity(x.shape[0]) * 1e-3
     ret, frontend_ret = helpers.test_frontend_function(
         input_dtypes=input_dtype,
@@ -890,18 +890,18 @@ def test_torch_svd(
     u, s, v = ret
     frontend_u, frontend_s, frontend_v = frontend_ret
 
-    if compute_uv:
+    if not some:
         helpers.assert_all_close(
-            ret_np=frontend_u @ np.diag(frontend_s) @ frontend_v.T,
-            ret_from_gt_np=u @ np.diag(s) @ v.T,
+            ret_np=np.asarray(frontend_u @ np.diag(frontend_s) @ frontend_v.T, dtype=np.float32),
+            ret_from_gt_np=np.asarray(u @ np.diag(s) @ v.T, dtype=np.float32),
             atol=1e-04,
             backend=backend_fw,
             ground_truth_backend=frontend,
         )
     else:
         helpers.assert_all_close(
-            ret_np=frontend_s,
-            ret_from_gt_np=s,
+            ret_np=np.asarray(frontend_u[...,:frontend_s.shape[0]] @ np.diag(frontend_s) @ frontend_v.T, dtype=np.float32),
+            ret_from_gt_np=np.asarray(u[...,:s.shape[0]] @ np.diag(s) @ v.T, dtype=np.float32),
             atol=1e-04,
             backend=backend_fw,
             ground_truth_backend=frontend,
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
index 7fae4e9765fda..f8310c28c310e 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
@@ -1270,7 +1270,7 @@ def test_torch_svd(
 ):
     dtype, x = dtype_and_x
     x = np.asarray(x[0], dtype=dtype[0])
-    # make symmetric positive definite beforehand
+    # make symmetric positive definite
     x = np.matmul(x.T, x) + np.identity(x.shape[0]) * 1e-3
     ret, frontend_ret = helpers.test_frontend_function(
         input_dtypes=dtype,
@@ -1283,22 +1283,22 @@ def test_torch_svd(
         A=x,
         full_matrices=full_matrices,
     )
-    ret = [ivy.to_numpy(x) for x in ret]
+    ret = [np.asarray(x) for x in ret]
     frontend_ret = [np.asarray(x) for x in frontend_ret]
     u, s, vh = ret
     frontend_u, frontend_s, frontend_vh = frontend_ret
     if full_matrices:
         helpers.assert_all_close(
-            ret_np=frontend_u[...,:frontend_s.shape[0]] @ np.diag(frontend_s) @ frontend_vh.T,
-            ret_from_gt_np=u[...,:s.shape[0]] @ np.diag(s) @ vh.T,
+            ret_np=np.asarray(frontend_u[...,:frontend_s.shape[0]] @ np.diag(frontend_s) @ frontend_vh, dtype=np.float32),
+            ret_from_gt_np=np.asarray(u[...,:s.shape[0]] @ np.diag(s) @ vh, dtype=np.float32),
             atol=1e-04,
             backend=backend_fw,
             ground_truth_backend=frontend,
         )
     else:
         helpers.assert_all_close(
-            ret_np=frontend_u @ np.diag(frontend_s) @ frontend_vh.T,
-            ret_from_gt_np=u @ np.diag(s) @ vh.T,
+            ret_np=np.asarray(frontend_u @ np.diag(frontend_s) @ frontend_vh, dtype=np.float32),
+            ret_from_gt_np=np.asarray(u @ np.diag(s) @ vh, dtype=np.float32),
             atol=1e-04,
             backend=backend_fw,
             ground_truth_backend=frontend,

From efe9a5ae405a6b9bd9e494617e78aa07e7099cf7 Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Thu, 4 Jul 2024 10:17:00 +0800
Subject: [PATCH 11/35] tests are partially passing, though for torch backend,
 "RuntimeError: Can't call numpy() on Tensor that requires grad. Use
 tensor.detach().numpy() instead. " happen

---
 .../test_jax/test_lax/test_linalg.py           | 18 ++++++++----------
 .../test_jax/test_numpy/test_linalg.py         |  3 +--
 .../test_linalg/test_decompositions.py         |  5 ++---
 .../test_tensorflow/test_linalg.py             |  3 ++-
 .../test_tensorflow/test_raw_ops.py            |  3 ++-
 .../test_torch/test_blas_and_lapack_ops.py     |  3 +--
 .../test_frontends/test_torch/test_linalg.py   |  5 +----
 .../test_frontends/test_torch/test_tensor.py   |  7 ++++---
 8 files changed, 21 insertions(+), 26 deletions(-)

diff --git a/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
index 74501eca12a5f..718ed905105a5 100644
--- a/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
@@ -159,6 +159,7 @@ def test_jax_qr(
 
 
 # svd
+# TODO: implement proper drawing of index parameter
 @handle_frontend_test(
     fn_tree="jax.lax.linalg.svd",
     dtype_x=helpers.dtype_and_values(
@@ -189,7 +190,7 @@ def test_jax_svd(
 ):
     dtype, x = dtype_and_x
     x = np.asarray(x[0], dtype=dtype[0])
-    # make symmetric positive-definite beforehand
+    # make symmetric positive-definite
     x = np.matmul(x.T, x) + np.identity(x.shape[0]) * 1e-3
 
     ret, frontend_ret = helpers.test_frontend_function(
@@ -205,18 +206,15 @@ def test_jax_svd(
         compute_uv=compute_uv,
         subset_by_index=index,
     )
-
+    ret = [np.asarray(x) for x in ret]
+    frontend_ret = [np.asarray(x) for x in frontend_ret]
     if compute_uv:
-        with BackendHandler.update_backend(backend_fw) as ivy_backend:
-            ret = [ivy_backend.to_numpy(x) for x in ret]
-        frontend_ret = [np.asarray(x) for x in frontend_ret]
-
-        u, s, vh = ret
-        frontend_u, frontend_s, frontend_vh = frontend_ret
+        u, s, v = ret
+        frontend_u, frontend_s, frontend_v = frontend_ret
 
         assert_all_close(
-            ret_np=u @ np.diag(s) @ vh,
-            ret_from_gt_np=frontend_u @ np.diag(frontend_s) @ frontend_vh,
+            ret_np=u @ np.diag(s) @ v.T,
+            ret_from_gt_np=frontend_u @ np.diag(frontend_s) @ frontend_v.T,
             rtol=1e-2,
             atol=1e-2,
             backend=backend_fw,
diff --git a/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py
index fb081e1cd406a..a5510c8ab68d1 100644
--- a/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py
@@ -881,9 +881,8 @@ def test_jax_svd(
 ):
     dtype, x = dtype_and_x
     x = np.asarray(x[0], dtype=dtype[0])
-    # make symmetric positive-definite beforehand
+    # make symmetric positive-definite
     x = np.matmul(x.T, x) + np.identity(x.shape[0]) * 1e-3
-
     ret, frontend_ret = helpers.test_frontend_function(
         input_dtypes=dtype,
         frontend=frontend,
diff --git a/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py b/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py
index f740b7278dacb..bf75c1359b3ae 100644
--- a/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py
+++ b/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py
@@ -105,9 +105,8 @@ def test_numpy_svd(
 ):
     dtype, x = dtype_and_x
     x = x[0]
-    x = (
-        np.matmul(x.T, x) + np.identity(x.shape[0]) * 1e-3
-    )  # make symmetric positive-definite
+    # make symmetric positive-definite
+    x = np.matmul(x.T, x) + np.identity(x.shape[0]) * 1e-3
     ret, ret_gt = helpers.test_frontend_function(
         input_dtypes=dtype,
         backend_to_test=backend_fw,
diff --git a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_linalg.py
index 24e4d61344997..882e886e8bf02 100644
--- a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_linalg.py
@@ -1070,6 +1070,7 @@ def test_tensorflow_solve(
     )
 
 
+# svd
 @handle_frontend_test(
     fn_tree="tensorflow.linalg.svd",
     dtype_and_x=helpers.dtype_and_values(
@@ -1094,7 +1095,7 @@ def test_tensorflow_svd(
 ):
     dtype, x = dtype_and_x
     x = np.asarray(x[0], dtype=dtype[0])
-    # make symmetric positive definite beforehand
+    # make symmetric positive definite
     x = np.matmul(x.T, x) + np.identity(x.shape[0]) * 1e-3
     ret, frontend_ret = helpers.test_frontend_function(
         input_dtypes=dtype,
diff --git a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py
index ad9b5ee4f3114..d82fc291df272 100644
--- a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py
@@ -4267,6 +4267,7 @@ def test_tensorflow_Sum(  # NOQA
     )
 
 
+# svd
 @handle_frontend_test(
     fn_tree="tensorflow.raw_ops.Svd",
     dtype_and_x=helpers.dtype_and_values(
@@ -4291,7 +4292,7 @@ def test_tensorflow_Svd(
 ):
     dtype, x = dtype_and_x
     x = np.asarray(x[0], dtype=dtype[0])
-    # make symmetric positive definite beforehand
+    # make symmetric positive definite
     x = np.matmul(x.T, x) + np.identity(x.shape[0]) * 1e-3
     ret, frontend_ret = helpers.test_frontend_function(
         input_dtypes=dtype,
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
index fa75313a9d24d..7ec03a6e822b1 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
@@ -852,8 +852,7 @@ def test_torch_qr(
         available_dtypes=helpers.get_dtypes("float"),
         min_value=0,
         max_value=10,
-        min_num_dims = 2,
-        max_num_dims = 5,
+        shape=helpers.ints(min_value=2, max_value=5).map(lambda x: (x, x)),
     ),
     some=st.booleans(),
     compute_uv=st.booleans(),
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
index f8310c28c310e..2d2cd71104f2e 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
@@ -1251,10 +1251,7 @@ def test_torch_solve_ex(
         available_dtypes=helpers.get_dtypes("float"),
         min_value=0,
         max_value=10,
-        min_num_dims=2,
-        max_num_dims=5,
-        min_dim_size=1,
-        max_dim_size=5,
+        shape=helpers.ints(min_value=2, max_value=5).map(lambda x: (x, x)),
     ),
     full_matrices=st.booleans(),
 )
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
index 10a8b3385fbf3..0029cfa3ca583 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
@@ -12866,6 +12866,7 @@ def test_torch_sum(
     )
 
 
+# svd
 @handle_frontend_method(
     class_tree=CLASS_TREE,
     init_tree="torch.tensor",
@@ -12892,7 +12893,8 @@ def test_torch_svd(
 ):
     input_dtype, x = dtype_and_x
     x = np.asarray(x[0], dtype=input_dtype[0])
-
+    # make symmetric positive-definite
+    x = np.matmul(x.T, x) + np.identity(x.shape[0]) * 1e-3
     ret, frontend_ret = helpers.test_frontend_method(
         init_input_dtypes=input_dtype,
         init_all_as_kwargs_np={
@@ -12911,8 +12913,7 @@ def test_torch_svd(
         on_device=on_device,
         test_values=False,
     )
-    with helpers.update_backend(backend_fw) as ivy_backend:
-        ret = [ivy_backend.to_numpy(x) for x in ret]
+    ret = [np.asarray(x) for x in ret]
     frontend_ret = [np.asarray(x) for x in frontend_ret]
 
     u, s, vh = ret

From 26aeba04824609e91c43d1d7fd4dbf77fd648982 Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Sun, 7 Jul 2024 14:37:55 +0800
Subject: [PATCH 12/35] fix test of numpy.linalg.decomposition.svd as it
 returns a svd object instead of the normal tuple and apply the np.asarray(x)
 change over ivy.as_numpy in other tests, ensure the different return pattern
 (s,u,v tha u,s,v)from tensorflow and when comput_uv is false get handled in
 the tests. Now only dtype mismatches happens

---
 .../frontends/numpy/linalg/decompositions.py  |  2 +-
 .../test_jax/test_lax/test_linalg.py          |  8 ++--
 .../test_jax/test_numpy/test_linalg.py        |  7 +---
 .../test_linalg/test_decompositions.py        | 39 ++++++++++++-------
 .../test_tensorflow/test_linalg.py            | 35 +++++++++++------
 .../test_tensorflow/test_raw_ops.py           | 36 ++++++++++-------
 6 files changed, 78 insertions(+), 49 deletions(-)

diff --git a/ivy/functional/frontends/numpy/linalg/decompositions.py b/ivy/functional/frontends/numpy/linalg/decompositions.py
index 0452e9c19a271..24bf8dda890d5 100644
--- a/ivy/functional/frontends/numpy/linalg/decompositions.py
+++ b/ivy/functional/frontends/numpy/linalg/decompositions.py
@@ -15,5 +15,5 @@ def qr(a, mode="reduced"):
 
 @to_ivy_arrays_and_back
 def svd(a, full_matrices=True, compute_uv=True, hermitian=False):
-    # Todo: conpute_uv and hermitian handling
+    # Todo: hermitian handling
     return ivy.svd(a, full_matrices=full_matrices, compute_uv=compute_uv)
diff --git a/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
index 718ed905105a5..27d4f7f738b09 100644
--- a/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
@@ -206,9 +206,9 @@ def test_jax_svd(
         compute_uv=compute_uv,
         subset_by_index=index,
     )
-    ret = [np.asarray(x) for x in ret]
-    frontend_ret = [np.asarray(x) for x in frontend_ret]
     if compute_uv:
+        ret = [np.asarray(x) for x in ret]
+        frontend_ret = [np.asarray(x) for x in frontend_ret]
         u, s, v = ret
         frontend_u, frontend_s, frontend_v = frontend_ret
 
@@ -221,11 +221,9 @@ def test_jax_svd(
             ground_truth_backend=frontend,
         )
     else:
-        with BackendHandler.update_backend(backend_fw) as ivy_backend:
-            ret = ivy_backend.to_numpy(ret)
         assert_all_close(
             ret_np=ret,
-            ret_from_gt_np=np.asarray(frontend_ret[0]),
+            ret_from_gt_np=frontend_ret,
             rtol=1e-2,
             atol=1e-2,
             backend=backend_fw,
diff --git a/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py
index a5510c8ab68d1..79ca88fc0456d 100644
--- a/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py
@@ -897,8 +897,7 @@ def test_jax_svd(
     )
 
     if compute_uv:
-        with BackendHandler.update_backend(backend_fw) as ivy_backend:
-            ret = [ivy_backend.to_numpy(x) for x in ret]
+        ret = [np.asarray(x) for x in ret]
         frontend_ret = [np.asarray(x) for x in frontend_ret]
 
         u, s, vh = ret
@@ -913,11 +912,9 @@ def test_jax_svd(
             ground_truth_backend=frontend,
         )
     else:
-        with BackendHandler.update_backend(backend_fw) as ivy_backend:
-            ret = ivy_backend.to_numpy(ret)
         assert_all_close(
             ret_np=ret,
-            ret_from_gt_np=np.asarray(frontend_ret[0]),
+            ret_from_gt_np=frontend_ret,
             rtol=1e-2,
             atol=1e-2,
             backend=backend_fw,
diff --git a/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py b/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py
index bf75c1359b3ae..44a67f6dd00ff 100644
--- a/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py
+++ b/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py
@@ -4,6 +4,7 @@
 from hypothesis import strategies as st
 
 # local
+import ivy
 import ivy_tests.test_ivy.helpers as helpers
 from ivy_tests.test_ivy.helpers import handle_frontend_test, BackendHandler
 from ivy_tests.test_ivy.test_functional.test_core.test_linalg import (
@@ -81,6 +82,7 @@ def test_numpy_qr(
 
 
 # svd
+# Todo: hermitian handling
 @handle_frontend_test(
     fn_tree="numpy.linalg.svd",
     dtype_and_x=helpers.dtype_and_values(
@@ -107,7 +109,7 @@ def test_numpy_svd(
     x = x[0]
     # make symmetric positive-definite
     x = np.matmul(x.T, x) + np.identity(x.shape[0]) * 1e-3
-    ret, ret_gt = helpers.test_frontend_function(
+    ret, frontend_ret = helpers.test_frontend_function(
         input_dtypes=dtype,
         backend_to_test=backend_fw,
         frontend=frontend,
@@ -119,15 +121,26 @@ def test_numpy_svd(
         full_matrices=full_matrices,
         compute_uv=compute_uv,
     )
-    with BackendHandler.update_backend(backend_fw) as ivy_backend:
-        for u, v in zip(ret, ret_gt):
-            u = ivy_backend.to_numpy(ivy_backend.abs(u))
-            v = ivy_backend.to_numpy(ivy_backend.abs(v))
-            helpers.value_test(
-                ret_np_flat=u,
-                ret_np_from_gt_flat=v,
-                rtol=1e-04,
-                atol=1e-04,
-                backend=backend_fw,
-                ground_truth_backend=frontend,
-            )
+    if compute_uv:
+        ret = [np.asarray(x) for x in ret]
+        frontend_ret = [np.asarray(x) for x in frontend_ret]
+        u, s, v = ret
+        frontend_u, frontend_s, frontend_v = frontend_ret
+
+        helpers.assert_all_close(
+            ret_np=u @ np.diag(s) @ v.T,
+            ret_from_gt_np=frontend_u @ np.diag(frontend_s) @ frontend_v.T,
+            rtol=1e-2,
+            atol=1e-2,
+            backend=backend_fw,
+            ground_truth_backend=frontend,
+        )
+    else:
+        helpers.assert_all_close(
+            ret_np=ret.S,
+            ret_from_gt_np=frontend_ret,
+            rtol=1e-2,
+            atol=1e-2,
+            backend=backend_fw,
+            ground_truth_backend=frontend,
+        )
diff --git a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_linalg.py
index 882e886e8bf02..3eca73117d088 100644
--- a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_linalg.py
@@ -1111,20 +1111,31 @@ def test_tensorflow_svd(
         full_matrices=full_matrices,
         compute_uv=compute_uv,
     )
-    ret = [ivy.to_numpy(x) for x in ret]
-    frontend_ret = [np.asarray(x) for x in frontend_ret]
 
-    u, s, vh = ret
-    frontend_s, frontend_u, frontend_vh = frontend_ret
+    if compute_uv:
+        ret = [np.asarray(x) for x in ret]
+        frontend_ret = [np.asarray(x) for x in frontend_ret]
 
-    assert_all_close(
-        ret_np=u @ np.diag(s) @ vh,
-        ret_from_gt_np=frontend_u @ np.diag(frontend_s) @ frontend_vh.T,
-        rtol=1e-2,
-        atol=1e-2,
-        ground_truth_backend=frontend,
-        backend=backend_fw,
-    )
+        s, u, v = ret
+        frontend_s, frontend_u, frontend_v = frontend_ret
+
+        assert_all_close(
+            ret_np=u @ np.diag(s) @ v.T,
+            ret_from_gt_np=frontend_u @ np.diag(frontend_s) @ frontend_v.T,
+            rtol=1e-2,
+            atol=1e-2,
+            backend=backend_fw,
+            ground_truth_backend=frontend,
+        )
+    else:
+        assert_all_close(
+            ret_np=ret,
+            ret_from_gt_np=frontend_ret,
+            rtol=1e-2,
+            atol=1e-2,
+            backend=backend_fw,
+            ground_truth_backend=frontend,
+        )
 
 
 # tensor_diag
diff --git a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py
index d82fc291df272..1c634f57fcb9e 100644
--- a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py
@@ -4306,20 +4306,30 @@ def test_tensorflow_Svd(
         full_matrices=full_matrices,
         compute_uv=compute_uv,
     )
-    ret = [ivy.to_numpy(x) for x in ret]
-    frontend_ret = [np.asarray(x) for x in frontend_ret]
 
-    u, s, vh = ret
-    frontend_s, frontend_u, frontend_vh = frontend_ret
-
-    assert_all_close(
-        ret_np=u @ np.diag(s) @ vh,
-        ret_from_gt_np=frontend_u @ np.diag(frontend_s) @ frontend_vh.T,
-        rtol=1e-2,
-        atol=1e-2,
-        ground_truth_backend=frontend,
-        backend=backend_fw,
-    )
+    if compute_uv:
+        ret = [np.asarray(x) for x in ret]
+        frontend_ret = [np.asarray(x) for x in frontend_ret]
+
+        s, u, v = ret
+        frontend_s, frontend_u, frontend_v = frontend_ret
+        assert_all_close(
+            ret_np=u @ np.diag(s) @ v.T,
+            ret_from_gt_np=frontend_u @ np.diag(frontend_s) @ frontend_v.T,
+            rtol=1e-2,
+            atol=1e-2,
+            backend=backend_fw,
+            ground_truth_backend=frontend,
+        )
+    else:
+        assert_all_close(
+            ret_np=s,
+            ret_from_gt_np=frontend_s,
+            rtol=1e-2,
+            atol=1e-2,
+            backend=backend_fw,
+            ground_truth_backend=frontend,
+        )
 
 
 # Tan

From 3bb5b667b123e8252d21870c06e5dc471edc26ad Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Mon, 15 Jul 2024 09:41:58 +0800
Subject: [PATCH 13/35] now only torch backend of jax.numpy.linalg.svd is
 failing due to "RuntimeError: Can't call numpy() on Tensor that requires
 grad. Use tensor.detach().numpy() instead." when the test function calls
 np.asarray to the returned value

---
 ivy/functional/frontends/jax/numpy/linalg.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/ivy/functional/frontends/jax/numpy/linalg.py b/ivy/functional/frontends/jax/numpy/linalg.py
index 57c69ee5b1596..1b978f64f5574 100644
--- a/ivy/functional/frontends/jax/numpy/linalg.py
+++ b/ivy/functional/frontends/jax/numpy/linalg.py
@@ -121,9 +121,11 @@ def solve(a, b):
 
 @to_ivy_arrays_and_back
 def svd(a, /, *, full_matrices=True, compute_uv=True, hermitian=None):
+    # TODO: handle hermitian
     if not compute_uv:
-        return ivy.svdvals(a)
-    return ivy.svd(a, full_matrices=full_matrices)
+        return ivy.svdvals(a).astype(ivy.float64)
+    ret = ivy.svd(a, full_matrices=full_matrices)
+    return tuple([ x.astype(ivy.float64) for x in ret])
 
 
 @to_ivy_arrays_and_back

From 8b29eb74597db0b363eef24fccdc89a0c224ae90 Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Mon, 15 Jul 2024 13:19:45 +0800
Subject: [PATCH 14/35] all tests for tesnorflow.linalg.svd are passing

---
 ivy/functional/frontends/jax/numpy/linalg.py              | 4 +---
 ivy/functional/frontends/tensorflow/linalg.py             | 7 ++++++-
 .../test_frontends/test_tensorflow/test_linalg.py         | 8 +++-----
 3 files changed, 10 insertions(+), 9 deletions(-)

diff --git a/ivy/functional/frontends/jax/numpy/linalg.py b/ivy/functional/frontends/jax/numpy/linalg.py
index 1b978f64f5574..79821e417d990 100644
--- a/ivy/functional/frontends/jax/numpy/linalg.py
+++ b/ivy/functional/frontends/jax/numpy/linalg.py
@@ -122,9 +122,7 @@ def solve(a, b):
 @to_ivy_arrays_and_back
 def svd(a, /, *, full_matrices=True, compute_uv=True, hermitian=None):
     # TODO: handle hermitian
-    if not compute_uv:
-        return ivy.svdvals(a).astype(ivy.float64)
-    ret = ivy.svd(a, full_matrices=full_matrices)
+    ret = ivy.svd(a, full_matrices=full_matrices, compute_uv=compute_uv)
     return tuple([ x.astype(ivy.float64) for x in ret])
 
 
diff --git a/ivy/functional/frontends/tensorflow/linalg.py b/ivy/functional/frontends/tensorflow/linalg.py
index 01a8f293f4497..fe797894f4aef 100644
--- a/ivy/functional/frontends/tensorflow/linalg.py
+++ b/ivy/functional/frontends/tensorflow/linalg.py
@@ -358,7 +358,12 @@ def solve(matrix, rhs, /, *, adjoint=False, name=None):
 
 @to_ivy_arrays_and_back
 def svd(a, /, *, full_matrices=False, compute_uv=True, name=None):
-    return ivy.svd(a, compute_uv=compute_uv, full_matrices=full_matrices)
+    if compute_uv:
+        svd = ivy.svd(a, compute_uv=compute_uv, full_matrices=full_matrices)
+        return tuple([ivy.astype(svd.S, ivy.float64), ivy.astype(svd.U, ivy.float64), ivy.astype(svd.Vh.T, ivy.float64)])
+    else:
+        svd = ivy.svd(a, compute_uv=compute_uv, full_matrices=full_matrices)
+        return ivy.astype(svd.S, ivy.float64)
 
 
 @to_ivy_arrays_and_back
diff --git a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_linalg.py
index 3eca73117d088..c6a62f6598367 100644
--- a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_linalg.py
@@ -1080,7 +1080,7 @@ def test_tensorflow_solve(
         shape=helpers.ints(min_value=2, max_value=5).map(lambda x: (x, x)),
     ),
     full_matrices=st.booleans(),
-    compute_uv=st.just(True),
+    compute_uv=st.booleans(),
 )
 def test_tensorflow_svd(
     *,
@@ -1105,8 +1105,6 @@ def test_tensorflow_svd(
         fn_tree=fn_tree,
         on_device=on_device,
         test_values=False,
-        atol=1e-03,
-        rtol=1e-05,
         a=x,
         full_matrices=full_matrices,
         compute_uv=compute_uv,
@@ -1129,8 +1127,8 @@ def test_tensorflow_svd(
         )
     else:
         assert_all_close(
-            ret_np=ret,
-            ret_from_gt_np=frontend_ret,
+            ret_np=np.asarray(ret),
+            ret_from_gt_np=np.asarray(frontend_ret),
             rtol=1e-2,
             atol=1e-2,
             backend=backend_fw,

From bc30d7d54ff8601784800c369d637e1752f49f70 Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Tue, 16 Jul 2024 08:31:07 +0800
Subject: [PATCH 15/35] try to fix the two svd function in torch frontend, now
 the only problem is that the ground truth returns a ivy array with dtype the
 same as input, while the function returns a torch tensor with the torch
 version of that dtype.

---
 .../test_torch/test_blas_and_lapack_ops.py    | 22 +++++++++++--------
 .../test_frontends/test_torch/test_linalg.py  | 10 ++++-----
 2 files changed, 17 insertions(+), 15 deletions(-)

diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
index 7ec03a6e822b1..1ff94bb431034 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
@@ -883,24 +883,28 @@ def test_torch_svd(
         some=some,
         compute_uv=compute_uv,
     )
-    ret = [np.asarray(x) for x in ret]
-    frontend_ret = [np.asarray(x) for x in frontend_ret]
-
     u, s, v = ret
     frontend_u, frontend_s, frontend_v = frontend_ret
-
-    if not some:
+    if not compute_uv:
+        helpers.assert_all_close(
+            ret_np=frontend_s.numpy(),
+            ret_from_gt_np=s,
+            atol=1e-04,
+            backend=backend_fw,
+            ground_truth_backend=frontend,
+        )
+    elif not some:
         helpers.assert_all_close(
-            ret_np=np.asarray(frontend_u @ np.diag(frontend_s) @ frontend_v.T, dtype=np.float32),
-            ret_from_gt_np=np.asarray(u @ np.diag(s) @ v.T, dtype=np.float32),
+            ret_np=np.asarray(frontend_u @ np.diag(frontend_s) @ frontend_v.T, dtype=np.float64),
+            ret_from_gt_np=np.asarray(u @ np.diag(s) @ v.T, dtype=np.float64),
             atol=1e-04,
             backend=backend_fw,
             ground_truth_backend=frontend,
         )
     else:
         helpers.assert_all_close(
-            ret_np=np.asarray(frontend_u[...,:frontend_s.shape[0]] @ np.diag(frontend_s) @ frontend_v.T, dtype=np.float32),
-            ret_from_gt_np=np.asarray(u[...,:s.shape[0]] @ np.diag(s) @ v.T, dtype=np.float32),
+            ret_np=np.asarray(frontend_u[...,:frontend_s.shape[0]] @ np.diag(frontend_s) @ frontend_v.T, dtype=np.float64),
+            ret_from_gt_np=np.asarray(u[...,:s.shape[0]] @ np.diag(s) @ v.T, dtype=np.float64),
             atol=1e-04,
             backend=backend_fw,
             ground_truth_backend=frontend,
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
index ffd8d4f44af7e..d7efd0ef9bbc2 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
@@ -1281,22 +1281,20 @@ def test_torch_svd(
         A=x,
         full_matrices=full_matrices,
     )
-    ret = [np.asarray(x) for x in ret]
-    frontend_ret = [np.asarray(x) for x in frontend_ret]
     u, s, vh = ret
     frontend_u, frontend_s, frontend_vh = frontend_ret
     if full_matrices:
         helpers.assert_all_close(
-            ret_np=np.asarray(frontend_u[...,:frontend_s.shape[0]] @ np.diag(frontend_s) @ frontend_vh, dtype=np.float32),
-            ret_from_gt_np=np.asarray(u[...,:s.shape[0]] @ np.diag(s) @ vh, dtype=np.float32),
+            ret_np=frontend_u[...,:frontend_s.shape[0]] @ np.diag(frontend_s) @ frontend_vh,
+            ret_from_gt_np=u[...,:s.shape[0]] @ np.diag(s) @ vh,
             atol=1e-04,
             backend=backend_fw,
             ground_truth_backend=frontend,
         )
     else:
         helpers.assert_all_close(
-            ret_np=np.asarray(frontend_u @ np.diag(frontend_s) @ frontend_vh, dtype=np.float32),
-            ret_from_gt_np=np.asarray(u @ np.diag(s) @ vh, dtype=np.float32),
+            ret_np=frontend_u @ np.diag(frontend_s) @ frontend_vh,
+            ret_from_gt_np=u @ np.diag(s) @ vh,
             atol=1e-04,
             backend=backend_fw,
             ground_truth_backend=frontend,

From bed8f77ea865d10b3039b0305813e2254b80bd7b Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Tue, 16 Jul 2024 08:57:07 +0800
Subject: [PATCH 16/35] applied the suggested fix to torch svd tests, they are
 all passing now

---
 .../test_torch/test_blas_and_lapack_ops.py      | 17 ++++++++++++-----
 .../test_frontends/test_torch/test_linalg.py    |  7 +++++++
 2 files changed, 19 insertions(+), 5 deletions(-)

diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
index 1ff94bb431034..206313798ff54 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
@@ -883,11 +883,18 @@ def test_torch_svd(
         some=some,
         compute_uv=compute_uv,
     )
+    if backend_fw == "torch":
+        frontend_ret = [x.detach() for x in frontend_ret]
+        ret = [x.detach() for x in frontend_ret]
+        ret = [np.asarray(x, dtype=np.dtype(getattr(np, input_dtype[0]))) for x in ret]
+    else:
+        ret = [np.asarray(x) for x in ret]
+    frontend_ret = [np.asarray(x, dtype=np.dtype(getattr(np, input_dtype[0]))) for x in frontend_ret]
     u, s, v = ret
     frontend_u, frontend_s, frontend_v = frontend_ret
     if not compute_uv:
         helpers.assert_all_close(
-            ret_np=frontend_s.numpy(),
+            ret_np=frontend_s,
             ret_from_gt_np=s,
             atol=1e-04,
             backend=backend_fw,
@@ -895,16 +902,16 @@ def test_torch_svd(
         )
     elif not some:
         helpers.assert_all_close(
-            ret_np=np.asarray(frontend_u @ np.diag(frontend_s) @ frontend_v.T, dtype=np.float64),
-            ret_from_gt_np=np.asarray(u @ np.diag(s) @ v.T, dtype=np.float64),
+            ret_np=frontend_u @ np.diag(frontend_s) @ frontend_v.T,
+            ret_from_gt_np=u @ np.diag(s) @ v.T,
             atol=1e-04,
             backend=backend_fw,
             ground_truth_backend=frontend,
         )
     else:
         helpers.assert_all_close(
-            ret_np=np.asarray(frontend_u[...,:frontend_s.shape[0]] @ np.diag(frontend_s) @ frontend_v.T, dtype=np.float64),
-            ret_from_gt_np=np.asarray(u[...,:s.shape[0]] @ np.diag(s) @ v.T, dtype=np.float64),
+            ret_np=frontend_u[...,:frontend_s.shape[0]] @ np.diag(frontend_s) @ frontend_v.T,
+            ret_from_gt_np=u[...,:s.shape[0]] @ np.diag(s) @ v.T,
             atol=1e-04,
             backend=backend_fw,
             ground_truth_backend=frontend,
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
index d7efd0ef9bbc2..b6d3b64f08af1 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
@@ -1281,6 +1281,13 @@ def test_torch_svd(
         A=x,
         full_matrices=full_matrices,
     )
+    if backend_fw == "torch":
+        frontend_ret = [x.detach() for x in frontend_ret]
+        ret = [x.detach() for x in frontend_ret]
+        ret = [np.asarray(x, dtype=np.dtype(getattr(np, dtype[0]))) for x in ret]
+    else:
+        ret = [np.asarray(x) for x in ret]
+    frontend_ret = [np.asarray(x, dtype=np.dtype(getattr(np, dtype[0]))) for x in frontend_ret]
     u, s, vh = ret
     frontend_u, frontend_s, frontend_vh = frontend_ret
     if full_matrices:

From 316986ededa8c9923dc7995ca933bcdb57e83f38 Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Tue, 16 Jul 2024 09:03:47 +0800
Subject: [PATCH 17/35] make namedtuple definition more simple as suggested

---
 ivy/functional/backends/jax/linear_algebra.py         | 2 +-
 ivy/functional/backends/numpy/linear_algebra.py       | 2 +-
 ivy/functional/backends/paddle/linear_algebra.py      | 2 +-
 ivy/functional/backends/tensorflow/linear_algebra.py  | 2 +-
 ivy/functional/backends/torch/linear_algebra.py       | 2 +-
 ivy/functional/frontends/torch/blas_and_lapack_ops.py | 2 +-
 6 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/ivy/functional/backends/jax/linear_algebra.py b/ivy/functional/backends/jax/linear_algebra.py
index 281ad7eb30315..3d032fffb9f98 100644
--- a/ivy/functional/backends/jax/linear_algebra.py
+++ b/ivy/functional/backends/jax/linear_algebra.py
@@ -361,7 +361,7 @@ def svd(
     x: JaxArray, /, *, compute_uv: bool = True, full_matrices: bool = True
 ) -> Union[JaxArray, Tuple[JaxArray, ...]]:
     if compute_uv:
-        results = namedtuple("svd", ['U', 'S', 'Vh'])
+        results = namedtuple("svd", 'U S Vh')
         U, D, VT = jnp.linalg.svd(x, full_matrices=full_matrices, compute_uv=compute_uv)
         return results(U, D, VT)
     else:
diff --git a/ivy/functional/backends/numpy/linear_algebra.py b/ivy/functional/backends/numpy/linear_algebra.py
index 50691e06cfac4..d580a469f4f66 100644
--- a/ivy/functional/backends/numpy/linear_algebra.py
+++ b/ivy/functional/backends/numpy/linear_algebra.py
@@ -291,7 +291,7 @@ def svd(
     x: np.ndarray, /, *, compute_uv: bool = True, full_matrices: bool = True
 ) -> Union[np.ndarray, Tuple[np.ndarray, ...]]:
     if compute_uv:
-        results = namedtuple("svd", ['U', 'S', 'Vh'])
+        results = namedtuple("svd", 'U S Vh')
         U, D, VT = np.linalg.svd(x, full_matrices=full_matrices, compute_uv=compute_uv)
         return results(U, D, VT)
     else:
diff --git a/ivy/functional/backends/paddle/linear_algebra.py b/ivy/functional/backends/paddle/linear_algebra.py
index 16cdce79c1a0b..5bbefe31838a9 100644
--- a/ivy/functional/backends/paddle/linear_algebra.py
+++ b/ivy/functional/backends/paddle/linear_algebra.py
@@ -521,7 +521,7 @@ def svd(
 ) -> Union[paddle.Tensor, Tuple[paddle.Tensor, ...]]:
     ret = paddle.linalg.svd(x, full_matrices=full_matrices)
     if compute_uv:
-        results = namedtuple("svd", ['U', 'S', 'Vh'])
+        results = namedtuple("svd", 'U S Vh')
         return results(*ret)
     else:
         results = namedtuple("svd", "S")
diff --git a/ivy/functional/backends/tensorflow/linear_algebra.py b/ivy/functional/backends/tensorflow/linear_algebra.py
index 39ff8647f1d8f..976c2fb132b05 100644
--- a/ivy/functional/backends/tensorflow/linear_algebra.py
+++ b/ivy/functional/backends/tensorflow/linear_algebra.py
@@ -545,7 +545,7 @@ def svd(
     compute_uv: bool = True,
 ) -> Union[Union[tf.Tensor, tf.Variable], Tuple[Union[tf.Tensor, tf.Variable], ...]]:
     if compute_uv:
-        results = namedtuple("svd", ['U', 'S', 'Vh'])
+        results = namedtuple("svd", 'U S Vh')
         batch_shape = tf.shape(x)[:-2]
         num_batch_dims = len(batch_shape)
         transpose_dims = list(range(num_batch_dims)) + [
diff --git a/ivy/functional/backends/torch/linear_algebra.py b/ivy/functional/backends/torch/linear_algebra.py
index 752d7b42c0959..26deaf8d25f66 100644
--- a/ivy/functional/backends/torch/linear_algebra.py
+++ b/ivy/functional/backends/torch/linear_algebra.py
@@ -414,7 +414,7 @@ def svd(
     x: torch.Tensor, /, *, full_matrices: bool = True, compute_uv: bool = True
 ) -> Union[torch.Tensor, Tuple[torch.Tensor, ...]]:
     if compute_uv:
-        results = namedtuple("svd", ['U', 'S', 'Vh'])
+        results = namedtuple("svd", 'U S Vh')
         U, D, VT = torch.linalg.svd(x, full_matrices=full_matrices)
         return results(U, D, VT)
     else:
diff --git a/ivy/functional/frontends/torch/blas_and_lapack_ops.py b/ivy/functional/frontends/torch/blas_and_lapack_ops.py
index 47249630a8c58..4ced2b61b24e8 100644
--- a/ivy/functional/frontends/torch/blas_and_lapack_ops.py
+++ b/ivy/functional/frontends/torch/blas_and_lapack_ops.py
@@ -193,7 +193,7 @@ def slogdet(A, *, out=None):
 @to_ivy_arrays_and_back
 def svd(input, some=True, compute_uv=True, *, out=None):
     retu = ivy.svd(input, full_matrices=not some, compute_uv=compute_uv)
-    results = namedtuple("svd", ['U', 'S', 'V'])
+    results = namedtuple("svd", 'U S V')
     if compute_uv:
         ret = results(retu[0], retu[1], ivy.adjoint(retu[2]))
     else:

From e0268c6709d2331ae1ac290e1a419eb2a8f20d2f Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Tue, 16 Jul 2024 12:55:30 +0800
Subject: [PATCH 18/35] tried to fix jax.lac.linalg.svd. p.s. there is no
 implementation of subset_by_index parameter. tensorflow,torch and paddle
 backends are all failing due to significant  value differences in only part
 of the reconstructed matrixes.

---
 .../test_jax/test_lax/test_linalg.py          | 57 +++++++++++--------
 1 file changed, 32 insertions(+), 25 deletions(-)

diff --git a/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
index 27d4f7f738b09..d44cd78bf60b3 100644
--- a/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
@@ -159,26 +159,25 @@ def test_jax_qr(
 
 
 # svd
-# TODO: implement proper drawing of index parameter
+# TODO: implement proper drawing of index parameter and implement subset_by_index
 @handle_frontend_test(
     fn_tree="jax.lax.linalg.svd",
     dtype_x=helpers.dtype_and_values(
         available_dtypes=helpers.get_dtypes("float"),
         min_value=0,
         max_value=10,
-        min_num_dims=2,
-        max_num_dims=5,
+        shape=helpers.ints(min_value=2, max_value=5).map(lambda x: (x, x)),
     ),
     full_matrices=st.booleans(),
     compute_uv=st.booleans(),
     index=st.one_of(
-        st.none(), st.tuples(st.integers(min_value=0, max_value=3), st.integers(min_value=3, max_value=5))
+        st.none() #, st.tuples(st.integers(min_value=0, max_value=3), st.integers(min_value=3, max_value=5))
     ),
     test_with_out=st.just(False),
 )
 def test_jax_svd(
     *,
-    dtype_and_x,
+    dtype_x,
     full_matrices,
     compute_uv,
     index,
@@ -188,11 +187,10 @@ def test_jax_svd(
     test_flags,
     backend_fw,
 ):
-    dtype, x = dtype_and_x
+    dtype, x = dtype_x
     x = np.asarray(x[0], dtype=dtype[0])
     # make symmetric positive-definite
     x = np.matmul(x.T, x) + np.identity(x.shape[0]) * 1e-3
-
     ret, frontend_ret = helpers.test_frontend_function(
         input_dtypes=dtype,
         backend_to_test=backend_fw,
@@ -206,26 +204,35 @@ def test_jax_svd(
         compute_uv=compute_uv,
         subset_by_index=index,
     )
-    if compute_uv:
-        ret = [np.asarray(x) for x in ret]
-        frontend_ret = [np.asarray(x) for x in frontend_ret]
-        u, s, v = ret
-        frontend_u, frontend_s, frontend_v = frontend_ret
-
+    if not compute_uv:
+        if backend_fw == "torch":
+            frontend_ret = frontend_ret.detach()
+            ret = ret.detach()
         assert_all_close(
-            ret_np=u @ np.diag(s) @ v.T,
-            ret_from_gt_np=frontend_u @ np.diag(frontend_s) @ frontend_v.T,
-            rtol=1e-2,
-            atol=1e-2,
+            ret_np=np.asarray(frontend_ret, dtype=np.dtype(getattr(np, dtype[0]))),
+            ret_from_gt_np=np.asarray(ret),
+            atol=1e-03,
             backend=backend_fw,
             ground_truth_backend=frontend,
         )
     else:
-        assert_all_close(
-            ret_np=ret,
-            ret_from_gt_np=frontend_ret,
-            rtol=1e-2,
-            atol=1e-2,
-            backend=backend_fw,
-            ground_truth_backend=frontend,
-        )
+        ret = [np.asarray(x) for x in ret]
+        frontend_ret = [np.asarray(x, dtype=np.dtype(getattr(np, dtype[0]))) for x in frontend_ret]
+        u, s, v = ret
+        frontend_u, frontend_s, frontend_v = frontend_ret
+        if full_matrices:
+            helpers.assert_all_close(
+                ret_np=frontend_u @ np.diag(frontend_s) @ frontend_v.T,
+                ret_from_gt_np=u @ np.diag(s) @ v.T,
+                atol=1e-03,
+                backend=backend_fw,
+                ground_truth_backend=frontend,
+            )
+        else:
+            helpers.assert_all_close(
+                ret_np=frontend_u[...,:frontend_s.shape[0]] @ np.diag(frontend_s) @ frontend_v.T,
+                ret_from_gt_np=u[...,:s.shape[0]] @ np.diag(s) @ v.T,
+                atol=1e-03,
+                backend=backend_fw,
+                ground_truth_backend=frontend,
+            )
\ No newline at end of file

From dcab2c1864f411e58bef5e6496d4943dff6d4205 Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Tue, 16 Jul 2024 16:00:47 +0800
Subject: [PATCH 19/35] fixed jax.numpy.linalg.svd, all tests are passing, but
 jax.lax.linalg.svd produces significant difference with compute_uv=True (like
 flipped signs) in the reconstructed matrixes for all backends. I suspect that
 the decomposition of jax.lax.linalg.svd is different from other similiar
 functions

---
 ivy/functional/frontends/jax/numpy/linalg.py  |  6 ++-
 .../test_jax/test_lax/test_linalg.py          |  7 ++--
 .../test_jax/test_numpy/test_linalg.py        | 38 +++++++++++--------
 3 files changed, 31 insertions(+), 20 deletions(-)

diff --git a/ivy/functional/frontends/jax/numpy/linalg.py b/ivy/functional/frontends/jax/numpy/linalg.py
index 79821e417d990..16bbaecfc8f39 100644
--- a/ivy/functional/frontends/jax/numpy/linalg.py
+++ b/ivy/functional/frontends/jax/numpy/linalg.py
@@ -123,7 +123,11 @@ def solve(a, b):
 def svd(a, /, *, full_matrices=True, compute_uv=True, hermitian=None):
     # TODO: handle hermitian
     ret = ivy.svd(a, full_matrices=full_matrices, compute_uv=compute_uv)
-    return tuple([ x.astype(ivy.float64) for x in ret])
+    if compute_uv:
+        return tuple(ret)
+    else:
+        return ivy.svdvals(a)
+
 
 
 @to_ivy_arrays_and_back
diff --git a/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
index d44cd78bf60b3..35e7496e03aeb 100644
--- a/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
@@ -206,7 +206,6 @@ def test_jax_svd(
     )
     if not compute_uv:
         if backend_fw == "torch":
-            frontend_ret = frontend_ret.detach()
             ret = ret.detach()
         assert_all_close(
             ret_np=np.asarray(frontend_ret, dtype=np.dtype(getattr(np, dtype[0]))),
@@ -216,6 +215,8 @@ def test_jax_svd(
             ground_truth_backend=frontend,
         )
     else:
+        if backend_fw == "torch":
+            ret = [x.detach() for x in ret]
         ret = [np.asarray(x) for x in ret]
         frontend_ret = [np.asarray(x, dtype=np.dtype(getattr(np, dtype[0]))) for x in frontend_ret]
         u, s, v = ret
@@ -224,7 +225,7 @@ def test_jax_svd(
             helpers.assert_all_close(
                 ret_np=frontend_u @ np.diag(frontend_s) @ frontend_v.T,
                 ret_from_gt_np=u @ np.diag(s) @ v.T,
-                atol=1e-03,
+                atol=1e-3,
                 backend=backend_fw,
                 ground_truth_backend=frontend,
             )
@@ -232,7 +233,7 @@ def test_jax_svd(
             helpers.assert_all_close(
                 ret_np=frontend_u[...,:frontend_s.shape[0]] @ np.diag(frontend_s) @ frontend_v.T,
                 ret_from_gt_np=u[...,:s.shape[0]] @ np.diag(s) @ v.T,
-                atol=1e-03,
+                atol=1e-3,
                 backend=backend_fw,
                 ground_truth_backend=frontend,
             )
\ No newline at end of file
diff --git a/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py
index 79ca88fc0456d..331891d684a8b 100644
--- a/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py
@@ -895,28 +895,34 @@ def test_jax_svd(
         full_matrices=full_matrices,
         compute_uv=compute_uv,
     )
-
     if compute_uv:
         ret = [np.asarray(x) for x in ret]
-        frontend_ret = [np.asarray(x) for x in frontend_ret]
-
+        frontend_ret = [np.asarray(x, dtype=np.dtype(getattr(np, dtype[0]))) for x in frontend_ret]
         u, s, vh = ret
         frontend_u, frontend_s, frontend_vh = frontend_ret
-
-        assert_all_close(
-            ret_np=u @ np.diag(s) @ vh,
-            ret_from_gt_np=frontend_u @ np.diag(frontend_s) @ frontend_vh,
-            rtol=1e-2,
-            atol=1e-2,
-            backend=backend_fw,
-            ground_truth_backend=frontend,
-        )
+        if full_matrices:
+            helpers.assert_all_close(
+                ret_np=frontend_u @ np.diag(frontend_s) @ frontend_vh,
+                ret_from_gt_np=u @ np.diag(s) @ vh,
+                atol=1e-3,
+                backend=backend_fw,
+                ground_truth_backend=frontend,
+            )
+        else:
+            helpers.assert_all_close(
+                ret_np=frontend_u[...,:frontend_s.shape[0]] @ np.diag(frontend_s) @ frontend_vh,
+                ret_from_gt_np=u[...,:s.shape[0]] @ np.diag(s) @ vh,
+                atol=1e-3,
+                backend=backend_fw,
+                ground_truth_backend=frontend,
+            )
     else:
+        if backend_fw == "torch":
+            ret = ret.detach()
         assert_all_close(
-            ret_np=ret,
-            ret_from_gt_np=frontend_ret,
-            rtol=1e-2,
-            atol=1e-2,
+            ret_np=np.asarray(frontend_ret, dtype=np.dtype(getattr(np, dtype[0]))),
+            ret_from_gt_np=np.asarray(ret),
+            atol=1e-3,
             backend=backend_fw,
             ground_truth_backend=frontend,
         )

From ac7a60afd6590036bafb3d039e3d69fe0062ec4d Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Thu, 18 Jul 2024 21:39:58 +0800
Subject: [PATCH 20/35] fixing numpy.linalg.decompositions.svd

---
 .../frontends/numpy/linalg/decompositions.py  |  5 ++-
 .../test_jax/test_lax/test_linalg.py          |  2 +-
 .../test_jax/test_numpy/test_linalg.py        |  2 +-
 .../test_linalg/test_decompositions.py        | 36 +++++++++++--------
 4 files changed, 27 insertions(+), 18 deletions(-)

diff --git a/ivy/functional/frontends/numpy/linalg/decompositions.py b/ivy/functional/frontends/numpy/linalg/decompositions.py
index 24bf8dda890d5..0e6dae20461c2 100644
--- a/ivy/functional/frontends/numpy/linalg/decompositions.py
+++ b/ivy/functional/frontends/numpy/linalg/decompositions.py
@@ -16,4 +16,7 @@ def qr(a, mode="reduced"):
 @to_ivy_arrays_and_back
 def svd(a, full_matrices=True, compute_uv=True, hermitian=False):
     # Todo: hermitian handling
-    return ivy.svd(a, full_matrices=full_matrices, compute_uv=compute_uv)
+    if compute_uv:
+        return ivy.svd(a, full_matrices=full_matrices, compute_uv=compute_uv)
+    else:
+        return ivy.astype(ivy.svdvals(a), a.dtype)
diff --git a/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
index 35e7496e03aeb..7cf8d69e6c6a0 100644
--- a/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
@@ -221,7 +221,7 @@ def test_jax_svd(
         frontend_ret = [np.asarray(x, dtype=np.dtype(getattr(np, dtype[0]))) for x in frontend_ret]
         u, s, v = ret
         frontend_u, frontend_s, frontend_v = frontend_ret
-        if full_matrices:
+        if not full_matrices:
             helpers.assert_all_close(
                 ret_np=frontend_u @ np.diag(frontend_s) @ frontend_v.T,
                 ret_from_gt_np=u @ np.diag(s) @ v.T,
diff --git a/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py
index 331891d684a8b..92c0e6148f831 100644
--- a/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py
@@ -900,7 +900,7 @@ def test_jax_svd(
         frontend_ret = [np.asarray(x, dtype=np.dtype(getattr(np, dtype[0]))) for x in frontend_ret]
         u, s, vh = ret
         frontend_u, frontend_s, frontend_vh = frontend_ret
-        if full_matrices:
+        if not full_matrices:
             helpers.assert_all_close(
                 ret_np=frontend_u @ np.diag(frontend_s) @ frontend_vh,
                 ret_from_gt_np=u @ np.diag(s) @ vh,
diff --git a/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py b/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py
index 44a67f6dd00ff..f806acc743a47 100644
--- a/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py
+++ b/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py
@@ -124,23 +124,29 @@ def test_numpy_svd(
     if compute_uv:
         ret = [np.asarray(x) for x in ret]
         frontend_ret = [np.asarray(x) for x in frontend_ret]
-        u, s, v = ret
-        frontend_u, frontend_s, frontend_v = frontend_ret
-
-        helpers.assert_all_close(
-            ret_np=u @ np.diag(s) @ v.T,
-            ret_from_gt_np=frontend_u @ np.diag(frontend_s) @ frontend_v.T,
-            rtol=1e-2,
-            atol=1e-2,
-            backend=backend_fw,
-            ground_truth_backend=frontend,
-        )
+        u, s, vh = ret
+        frontend_u, frontend_s, frontend_vh = frontend_ret
+        if not full_matrices:
+            helpers.assert_all_close(
+                ret_np=frontend_u @ np.diag(frontend_s) @ frontend_vh,
+                ret_from_gt_np=u @ np.diag(s) @ vh,
+                atol=1e-3,
+                backend=backend_fw,
+                ground_truth_backend=frontend,
+            )
+        else:
+            helpers.assert_all_close(
+                ret_np=frontend_u[...,:frontend_s.shape[0]] @ np.diag(frontend_s) @ frontend_vh,
+                ret_from_gt_np=u[...,:s.shape[0]] @ np.diag(s) @ vh,
+                atol=1e-3,
+                backend=backend_fw,
+                ground_truth_backend=frontend,
+            )
     else:
         helpers.assert_all_close(
-            ret_np=ret.S,
-            ret_from_gt_np=frontend_ret,
-            rtol=1e-2,
-            atol=1e-2,
+            ret_np=frontend_ret,
+            ret_from_gt_np=ret,
+            atol=1e-3,
             backend=backend_fw,
             ground_truth_backend=frontend,
         )

From 8e927a41dde4ddf442ca1e10706c9da87f8637ed Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Fri, 16 Aug 2024 06:08:54 +0000
Subject: [PATCH 21/35] fixed
 ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py::test_torch_svd,
 all tests passed

---
 .../test_frontends/test_torch/test_tensor.py  | 31 ++++++++++++-------
 1 file changed, 19 insertions(+), 12 deletions(-)

diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
index 8c690b5aac4c0..c9c63f85686c3 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
@@ -13146,24 +13146,31 @@ def test_torch_svd(
     ret = [np.asarray(x) for x in ret]
     frontend_ret = [np.asarray(x) for x in frontend_ret]
 
-    u, s, vh = ret
-    frontend_u, frontend_s, frontend_vh = frontend_ret
-
-    if compute_uv:
+    u, s, v = ret
+    frontend_u, frontend_s, frontend_v = frontend_ret
+    if not compute_uv:
         helpers.assert_all_close(
-            ret_np=frontend_u @ np.diag(frontend_s) @ frontend_vh.T,
-            ret_from_gt_np=u @ np.diag(s) @ vh,
-            rtol=1e-2,
-            atol=1e-2,
+            ret_np=frontend_s,
+            ret_from_gt_np=s,
+            atol=1e-04,
+            backend=backend_fw,
+            ground_truth_backend=frontend,
+        )
+    elif not some:
+        helpers.assert_all_close(
+            ret_np=frontend_u @ np.diag(frontend_s) @ frontend_v.T,
+            ret_from_gt_np=u @ np.diag(s) @ v.T,
+            atol=1e-04,
             backend=backend_fw,
             ground_truth_backend=frontend,
         )
     else:
         helpers.assert_all_close(
-            ret_np=frontend_s,
-            ret_from_gt_np=s,
-            rtol=1e-2,
-            atol=1e-2,
+            ret_np=frontend_u[..., : frontend_s.shape[0]]
+            @ np.diag(frontend_s)
+            @ frontend_v.T,
+            ret_from_gt_np=u[..., : s.shape[0]] @ np.diag(s) @ v.T,
+            atol=1e-04,
             backend=backend_fw,
             ground_truth_backend=frontend,
         )

From 37272a888cc861e6301bef05ef454d1317e504c3 Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Fri, 16 Aug 2024 12:21:41 +0000
Subject: [PATCH 22/35] fixed
 ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py::test_numpy_svd,
 though seems like using ivy.astype to convert type does not work at all

---
 .../frontends/numpy/linalg/decompositions.py        |  2 +-
 .../test_numpy/test_linalg/test_decompositions.py   | 13 +++++++------
 .../test_torch/test_blas_and_lapack_ops.py          | 13 +++++++------
 3 files changed, 15 insertions(+), 13 deletions(-)

diff --git a/ivy/functional/frontends/numpy/linalg/decompositions.py b/ivy/functional/frontends/numpy/linalg/decompositions.py
index 0e6dae20461c2..927096f08476a 100644
--- a/ivy/functional/frontends/numpy/linalg/decompositions.py
+++ b/ivy/functional/frontends/numpy/linalg/decompositions.py
@@ -15,7 +15,7 @@ def qr(a, mode="reduced"):
 
 @to_ivy_arrays_and_back
 def svd(a, full_matrices=True, compute_uv=True, hermitian=False):
-    # Todo: hermitian handling
+    # Todo: hermitian handling, ivy.astype does not work for some reason
     if compute_uv:
         return ivy.svd(a, full_matrices=full_matrices, compute_uv=compute_uv)
     else:
diff --git a/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py b/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py
index f806acc743a47..d7909c88d9fa2 100644
--- a/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py
+++ b/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py
@@ -4,9 +4,8 @@
 from hypothesis import strategies as st
 
 # local
-import ivy
 import ivy_tests.test_ivy.helpers as helpers
-from ivy_tests.test_ivy.helpers import handle_frontend_test, BackendHandler
+from ivy_tests.test_ivy.helpers import handle_frontend_test
 from ivy_tests.test_ivy.test_functional.test_core.test_linalg import (
     _get_dtype_and_matrix,
 )
@@ -123,7 +122,7 @@ def test_numpy_svd(
     )
     if compute_uv:
         ret = [np.asarray(x) for x in ret]
-        frontend_ret = [np.asarray(x) for x in frontend_ret]
+        frontend_ret = [np.asarray(x).astype(dtype[0]) for x in frontend_ret]
         u, s, vh = ret
         frontend_u, frontend_s, frontend_vh = frontend_ret
         if not full_matrices:
@@ -136,15 +135,17 @@ def test_numpy_svd(
             )
         else:
             helpers.assert_all_close(
-                ret_np=frontend_u[...,:frontend_s.shape[0]] @ np.diag(frontend_s) @ frontend_vh,
-                ret_from_gt_np=u[...,:s.shape[0]] @ np.diag(s) @ vh,
+                ret_np=frontend_u[..., : frontend_s.shape[0]]
+                @ np.diag(frontend_s)
+                @ frontend_vh,
+                ret_from_gt_np=u[..., : s.shape[0]] @ np.diag(s) @ vh,
                 atol=1e-3,
                 backend=backend_fw,
                 ground_truth_backend=frontend,
             )
     else:
         helpers.assert_all_close(
-            ret_np=frontend_ret,
+            ret_np=frontend_ret.astype(dtype[0]),
             ret_from_gt_np=ret,
             atol=1e-3,
             backend=backend_fw,
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
index 206313798ff54..1f86b0a825963 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
@@ -4,7 +4,6 @@
 from hypothesis import strategies as st, assume
 
 # local
-import ivy
 import ivy_tests.test_ivy.helpers as helpers
 from ivy_tests.test_ivy.helpers import handle_frontend_test
 from ivy_tests.test_ivy.helpers.hypothesis_helpers.general_helpers import (
@@ -879,17 +878,17 @@ def test_torch_svd(
         fn_tree=fn_tree,
         on_device=on_device,
         test_values=False,
-        input = x,
+        input=x,
         some=some,
         compute_uv=compute_uv,
     )
     if backend_fw == "torch":
         frontend_ret = [x.detach() for x in frontend_ret]
         ret = [x.detach() for x in frontend_ret]
-        ret = [np.asarray(x, dtype=np.dtype(getattr(np, input_dtype[0]))) for x in ret]
+        ret = [np.asarray(x) for x in ret]
     else:
         ret = [np.asarray(x) for x in ret]
-    frontend_ret = [np.asarray(x, dtype=np.dtype(getattr(np, input_dtype[0]))) for x in frontend_ret]
+    frontend_ret = [np.asarray(x).astype(input_dtype[0]) for x in frontend_ret]
     u, s, v = ret
     frontend_u, frontend_s, frontend_v = frontend_ret
     if not compute_uv:
@@ -910,8 +909,10 @@ def test_torch_svd(
         )
     else:
         helpers.assert_all_close(
-            ret_np=frontend_u[...,:frontend_s.shape[0]] @ np.diag(frontend_s) @ frontend_v.T,
-            ret_from_gt_np=u[...,:s.shape[0]] @ np.diag(s) @ v.T,
+            ret_np=frontend_u[..., : frontend_s.shape[0]]
+            @ np.diag(frontend_s)
+            @ frontend_v.T,
+            ret_from_gt_np=u[..., : s.shape[0]] @ np.diag(s) @ v.T,
             atol=1e-04,
             backend=backend_fw,
             ground_truth_backend=frontend,

From dc90073b324bbd1959a217c8987f07b0f00adf57 Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Sun, 18 Aug 2024 07:04:47 +0000
Subject: [PATCH 23/35] Fixing
 ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py::test_tensorflow_Svd,
 now the frontend somehow always return float64 nomatter input dtype

---
 .../frontends/tensorflow/raw_ops.py           |  9 ++--
 .../test_linalg/test_decompositions.py        |  4 +-
 .../test_tensorflow/test_raw_ops.py           | 42 +++++++++++--------
 .../test_torch/test_blas_and_lapack_ops.py    |  2 +-
 .../test_frontends/test_torch/test_tensor.py  |  2 +-
 5 files changed, 35 insertions(+), 24 deletions(-)

diff --git a/ivy/functional/frontends/tensorflow/raw_ops.py b/ivy/functional/frontends/tensorflow/raw_ops.py
index 61c87dcb5c76b..0128e89695fca 100644
--- a/ivy/functional/frontends/tensorflow/raw_ops.py
+++ b/ivy/functional/frontends/tensorflow/raw_ops.py
@@ -832,12 +832,15 @@ def Sum(*, input, axis, keep_dims=False, name="Sum"):
 
 
 @with_supported_dtypes(
-    {"2.15.0 and below": ("float64", "float128", "halfcomplex64", "complex128")},
+    {"2.15.0 and below": ("float64", "float32", "half", "complex64", "complex128")},
     "tensorflow",
 )
 @to_ivy_arrays_and_back
-def Svd(*, input, full_matrices=False, compute_uv=True, name=None):
-    return ivy.svd(input, compute_uv=compute_uv, full_matrices=full_matrices)
+def Svd(*, input, full_matrices=False, compute_uv=True, name="Svd"):
+    ret = ivy.svd(input, compute_uv=compute_uv, full_matrices=full_matrices)
+    if not compute_uv:
+        return (ret.S, None, None)
+    return (ret.S, ret.U, ivy.adjoint(ret.Vh))
 
 
 @to_ivy_arrays_and_back
diff --git a/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py b/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py
index d7909c88d9fa2..1e43a8a4e866c 100644
--- a/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py
+++ b/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py
@@ -85,7 +85,7 @@ def test_numpy_qr(
 @handle_frontend_test(
     fn_tree="numpy.linalg.svd",
     dtype_and_x=helpers.dtype_and_values(
-        available_dtypes=helpers.get_dtypes("float"),
+        available_dtypes=helpers.get_dtypes("valid"),
         min_value=0.1,
         max_value=10,
         shape=helpers.ints(min_value=2, max_value=5).map(lambda x: (x, x)),
@@ -105,7 +105,7 @@ def test_numpy_svd(
     on_device,
 ):
     dtype, x = dtype_and_x
-    x = x[0]
+    x = np.asarray(x[0], dtype=dtype[0])
     # make symmetric positive-definite
     x = np.matmul(x.T, x) + np.identity(x.shape[0]) * 1e-3
     ret, frontend_ret = helpers.test_frontend_function(
diff --git a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py
index 1c634f57fcb9e..b0f40ec0b440e 100644
--- a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py
@@ -4277,7 +4277,7 @@ def test_tensorflow_Sum(  # NOQA
         shape=helpers.ints(min_value=2, max_value=5).map(lambda x: (x, x)),
     ),
     full_matrices=st.booleans(),
-    compute_uv=st.just(True),
+    compute_uv=st.booleans(),
 )
 def test_tensorflow_Svd(
     *,
@@ -4306,25 +4306,33 @@ def test_tensorflow_Svd(
         full_matrices=full_matrices,
         compute_uv=compute_uv,
     )
-
+    ret = [np.asarray(x) for x in ret]
+    frontend_ret = [np.asarray(x) for x in frontend_ret]
+    s, u, v = ret
+    frontend_s, frontend_u, frontend_v = frontend_ret
     if compute_uv:
-        ret = [np.asarray(x) for x in ret]
-        frontend_ret = [np.asarray(x) for x in frontend_ret]
-
-        s, u, v = ret
-        frontend_s, frontend_u, frontend_v = frontend_ret
-        assert_all_close(
-            ret_np=u @ np.diag(s) @ v.T,
-            ret_from_gt_np=frontend_u @ np.diag(frontend_s) @ frontend_v.T,
-            rtol=1e-2,
-            atol=1e-2,
-            backend=backend_fw,
-            ground_truth_backend=frontend,
-        )
+        if not full_matrices:
+            helpers.assert_all_close(
+                ret_np=frontend_u @ np.diag(frontend_s) @ frontend_v.T,
+                ret_from_gt_np=u @ np.diag(s) @ v.T,
+                atol=1e-04,
+                backend=backend_fw,
+                ground_truth_backend=frontend,
+            )
+        else:
+            helpers.assert_all_close(
+                ret_np=frontend_u[..., : frontend_s.shape[0]]
+                @ np.diag(frontend_s)
+                @ frontend_v.T,
+                ret_from_gt_np=u[..., : s.shape[0]] @ np.diag(s) @ v.T,
+                atol=1e-04,
+                backend=backend_fw,
+                ground_truth_backend=frontend,
+            )
     else:
         assert_all_close(
-            ret_np=s,
-            ret_from_gt_np=frontend_s,
+            ret_np=frontend_s,
+            ret_from_gt_np=s,
             rtol=1e-2,
             atol=1e-2,
             backend=backend_fw,
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
index 1f86b0a825963..250874089d456 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
@@ -848,7 +848,7 @@ def test_torch_qr(
 @handle_frontend_test(
     fn_tree="torch.svd",
     dtype_and_x=helpers.dtype_and_values(
-        available_dtypes=helpers.get_dtypes("float"),
+        available_dtypes=helpers.get_dtypes("valid"),
         min_value=0,
         max_value=10,
         shape=helpers.ints(min_value=2, max_value=5).map(lambda x: (x, x)),
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
index c9c63f85686c3..0640f82060abc 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
@@ -13102,7 +13102,7 @@ def test_torch_sum(
     init_tree="torch.tensor",
     method_name="svd",
     dtype_and_x=helpers.dtype_and_values(
-        available_dtypes=helpers.get_dtypes("float"),
+        available_dtypes=helpers.get_dtypes("valid"),
         min_value=0,
         max_value=10,
         shape=helpers.ints(min_value=2, max_value=5).map(lambda x: (x, x)),

From 65c902fc059833bf78698e96514272f971c778a4 Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Tue, 20 Aug 2024 07:04:22 +0000
Subject: [PATCH 24/35] fixed
 ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py::test_jax_svd

---
 ivy/functional/frontends/jax/numpy/linalg.py  |  2 +-
 .../test_jax/test_numpy/test_linalg.py        | 23 +++++++++++--------
 .../test_torch/test_blas_and_lapack_ops.py    |  4 +---
 3 files changed, 15 insertions(+), 14 deletions(-)

diff --git a/ivy/functional/frontends/jax/numpy/linalg.py b/ivy/functional/frontends/jax/numpy/linalg.py
index 16bbaecfc8f39..993d8a8328cee 100644
--- a/ivy/functional/frontends/jax/numpy/linalg.py
+++ b/ivy/functional/frontends/jax/numpy/linalg.py
@@ -120,6 +120,7 @@ def solve(a, b):
 
 
 @to_ivy_arrays_and_back
+@with_unsupported_dtypes({"0.4.24 and below": ("float16", "bfloat16")}, "jax")
 def svd(a, /, *, full_matrices=True, compute_uv=True, hermitian=None):
     # TODO: handle hermitian
     ret = ivy.svd(a, full_matrices=full_matrices, compute_uv=compute_uv)
@@ -129,7 +130,6 @@ def svd(a, /, *, full_matrices=True, compute_uv=True, hermitian=None):
         return ivy.svdvals(a)
 
 
-
 @to_ivy_arrays_and_back
 @with_unsupported_dtypes({"0.4.24 and below": ("float16", "bfloat16")}, "jax")
 def tensorinv(a, ind=2):
diff --git a/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py
index 92c0e6148f831..ea390e6526aed 100644
--- a/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py
@@ -858,12 +858,7 @@ def test_jax_solve(
         min_value=0,
         max_value=10,
         shape=helpers.ints(min_value=2, max_value=5).map(lambda x: (x, x)),
-    ).filter(
-        lambda x: "float16" not in x[0]
-        and "bfloat16" not in x[0]
-        and np.linalg.cond(x[1][0]) < 1 / sys.float_info.epsilon
-        and np.linalg.det(np.asarray(x[1][0])) != 0
-    ),
+    ).filter(lambda x: "float16" not in x[0] and "bfloat16" not in x[0]),
     full_matrices=st.booleans(),
     compute_uv=st.booleans(),
     test_with_out=st.just(False),
@@ -896,8 +891,14 @@ def test_jax_svd(
         compute_uv=compute_uv,
     )
     if compute_uv:
-        ret = [np.asarray(x) for x in ret]
-        frontend_ret = [np.asarray(x, dtype=np.dtype(getattr(np, dtype[0]))) for x in frontend_ret]
+        if backend_fw == "torch":
+            frontend_ret = [
+                x for x in frontend_ret
+            ]  # unpack jaxlib.xla_extension.ArrayImpl as it is no .detach()
+            ret = [x for x in frontend_ret]
+        detyp = np.dtype(getattr(np, dtype[0]))
+        ret = [np.asarray(x).astype(detyp) for x in ret]
+        frontend_ret = [np.asarray(x, dtype=detyp) for x in frontend_ret]
         u, s, vh = ret
         frontend_u, frontend_s, frontend_vh = frontend_ret
         if not full_matrices:
@@ -910,8 +911,10 @@ def test_jax_svd(
             )
         else:
             helpers.assert_all_close(
-                ret_np=frontend_u[...,:frontend_s.shape[0]] @ np.diag(frontend_s) @ frontend_vh,
-                ret_from_gt_np=u[...,:s.shape[0]] @ np.diag(s) @ vh,
+                ret_np=frontend_u[..., : frontend_s.shape[0]]
+                @ np.diag(frontend_s)
+                @ frontend_vh,
+                ret_from_gt_np=u[..., : s.shape[0]] @ np.diag(s) @ vh,
                 atol=1e-3,
                 backend=backend_fw,
                 ground_truth_backend=frontend,
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
index 250874089d456..b84819a5de224 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
@@ -885,9 +885,7 @@ def test_torch_svd(
     if backend_fw == "torch":
         frontend_ret = [x.detach() for x in frontend_ret]
         ret = [x.detach() for x in frontend_ret]
-        ret = [np.asarray(x) for x in ret]
-    else:
-        ret = [np.asarray(x) for x in ret]
+    ret = [np.asarray(x) for x in ret]
     frontend_ret = [np.asarray(x).astype(input_dtype[0]) for x in frontend_ret]
     u, s, v = ret
     frontend_u, frontend_s, frontend_v = frontend_ret

From c92b6be00433b1432adec350fb6dc4c5e3d156a0 Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Tue, 20 Aug 2024 11:00:17 +0000
Subject: [PATCH 25/35] fixing
 ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py::test_tensorflow_Svd,
 though if input is complex number the results show large difference

---
 .../test_jax/test_lax/test_linalg.py          | 23 ++++++++++++-------
 .../test_tensorflow/test_raw_ops.py           | 22 ++++++++++++------
 .../test_torch/test_blas_and_lapack_ops.py    |  2 +-
 .../test_frontends/test_torch/test_linalg.py  | 13 +++++++----
 4 files changed, 39 insertions(+), 21 deletions(-)

diff --git a/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
index 7cf8d69e6c6a0..d25a5ec3858f2 100644
--- a/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
@@ -160,6 +160,7 @@ def test_jax_qr(
 
 # svd
 # TODO: implement proper drawing of index parameter and implement subset_by_index
+# and to resolve groundtruth's significant inaccuracy
 @handle_frontend_test(
     fn_tree="jax.lax.linalg.svd",
     dtype_x=helpers.dtype_and_values(
@@ -171,7 +172,9 @@ def test_jax_qr(
     full_matrices=st.booleans(),
     compute_uv=st.booleans(),
     index=st.one_of(
-        st.none() #, st.tuples(st.integers(min_value=0, max_value=3), st.integers(min_value=3, max_value=5))
+        st.none()
+        # , st.tuples(st.integers(min_value=0, max_value=3),
+        # st.integers(min_value=3, max_value=5))
     ),
     test_with_out=st.just(False),
 )
@@ -210,7 +213,7 @@ def test_jax_svd(
         assert_all_close(
             ret_np=np.asarray(frontend_ret, dtype=np.dtype(getattr(np, dtype[0]))),
             ret_from_gt_np=np.asarray(ret),
-            atol=1e-03,
+            rtol=1e-3,
             backend=backend_fw,
             ground_truth_backend=frontend,
         )
@@ -218,22 +221,26 @@ def test_jax_svd(
         if backend_fw == "torch":
             ret = [x.detach() for x in ret]
         ret = [np.asarray(x) for x in ret]
-        frontend_ret = [np.asarray(x, dtype=np.dtype(getattr(np, dtype[0]))) for x in frontend_ret]
+        frontend_ret = [
+            np.asarray(x, dtype=np.dtype(getattr(np, dtype[0]))) for x in frontend_ret
+        ]
         u, s, v = ret
         frontend_u, frontend_s, frontend_v = frontend_ret
         if not full_matrices:
             helpers.assert_all_close(
                 ret_np=frontend_u @ np.diag(frontend_s) @ frontend_v.T,
                 ret_from_gt_np=u @ np.diag(s) @ v.T,
-                atol=1e-3,
+                rtol=1e-3,
                 backend=backend_fw,
                 ground_truth_backend=frontend,
             )
         else:
             helpers.assert_all_close(
-                ret_np=frontend_u[...,:frontend_s.shape[0]] @ np.diag(frontend_s) @ frontend_v.T,
-                ret_from_gt_np=u[...,:s.shape[0]] @ np.diag(s) @ v.T,
-                atol=1e-3,
+                ret_np=frontend_u[..., : frontend_s.shape[0]]
+                @ np.diag(frontend_s)
+                @ frontend_v.T,
+                ret_from_gt_np=u[..., : s.shape[0]] @ np.diag(s) @ v.T,
+                rtol=1e-3,
                 backend=backend_fw,
                 ground_truth_backend=frontend,
-            )
\ No newline at end of file
+            )
diff --git a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py
index b0f40ec0b440e..b312ac1bc7b6e 100644
--- a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py
@@ -4272,7 +4272,7 @@ def test_tensorflow_Sum(  # NOQA
     fn_tree="tensorflow.raw_ops.Svd",
     dtype_and_x=helpers.dtype_and_values(
         available_dtypes=helpers.get_dtypes("valid"),
-        min_value=0,
+        min_value=0.1,
         max_value=10,
         shape=helpers.ints(min_value=2, max_value=5).map(lambda x: (x, x)),
     ),
@@ -4294,6 +4294,7 @@ def test_tensorflow_Svd(
     x = np.asarray(x[0], dtype=dtype[0])
     # make symmetric positive definite
     x = np.matmul(x.T, x) + np.identity(x.shape[0]) * 1e-3
+    x = x.astype(dtype[0])
     ret, frontend_ret = helpers.test_frontend_function(
         input_dtypes=dtype,
         backend_to_test=backend_fw,
@@ -4306,8 +4307,13 @@ def test_tensorflow_Svd(
         full_matrices=full_matrices,
         compute_uv=compute_uv,
     )
+    if backend_fw == "torch":
+        if not compute_uv:
+            ret = [ret[0].detach(), None, None]
+        else:
+            ret = [x.detach() for x in ret]
     ret = [np.asarray(x) for x in ret]
-    frontend_ret = [np.asarray(x) for x in frontend_ret]
+    frontend_ret = [np.asarray(x).astype(dtype[0]) for x in frontend_ret]
     s, u, v = ret
     frontend_s, frontend_u, frontend_v = frontend_ret
     if compute_uv:
@@ -4315,7 +4321,8 @@ def test_tensorflow_Svd(
             helpers.assert_all_close(
                 ret_np=frontend_u @ np.diag(frontend_s) @ frontend_v.T,
                 ret_from_gt_np=u @ np.diag(s) @ v.T,
-                atol=1e-04,
+                rtol=1e-3,
+                atol=1e-3,
                 backend=backend_fw,
                 ground_truth_backend=frontend,
             )
@@ -4325,16 +4332,17 @@ def test_tensorflow_Svd(
                 @ np.diag(frontend_s)
                 @ frontend_v.T,
                 ret_from_gt_np=u[..., : s.shape[0]] @ np.diag(s) @ v.T,
-                atol=1e-04,
+                rtol=1e-3,
+                atol=1e-3,
                 backend=backend_fw,
                 ground_truth_backend=frontend,
             )
     else:
         assert_all_close(
             ret_np=frontend_s,
-            ret_from_gt_np=s,
-            rtol=1e-2,
-            atol=1e-2,
+            ret_from_gt_np=s.astype(dtype[0]),
+            rtol=1e-3,
+            atol=1e-3,
             backend=backend_fw,
             ground_truth_backend=frontend,
         )
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
index b84819a5de224..a9580069cb512 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
@@ -884,7 +884,7 @@ def test_torch_svd(
     )
     if backend_fw == "torch":
         frontend_ret = [x.detach() for x in frontend_ret]
-        ret = [x.detach() for x in frontend_ret]
+        ret = [x.detach() for x in ret]
     ret = [np.asarray(x) for x in ret]
     frontend_ret = [np.asarray(x).astype(input_dtype[0]) for x in frontend_ret]
     u, s, v = ret
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
index b6d3b64f08af1..6884f2864148a 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
@@ -1283,17 +1283,21 @@ def test_torch_svd(
     )
     if backend_fw == "torch":
         frontend_ret = [x.detach() for x in frontend_ret]
-        ret = [x.detach() for x in frontend_ret]
+        ret = [x.detach() for x in ret]
         ret = [np.asarray(x, dtype=np.dtype(getattr(np, dtype[0]))) for x in ret]
     else:
         ret = [np.asarray(x) for x in ret]
-    frontend_ret = [np.asarray(x, dtype=np.dtype(getattr(np, dtype[0]))) for x in frontend_ret]
+    frontend_ret = [
+        np.asarray(x, dtype=np.dtype(getattr(np, dtype[0]))) for x in frontend_ret
+    ]
     u, s, vh = ret
     frontend_u, frontend_s, frontend_vh = frontend_ret
     if full_matrices:
         helpers.assert_all_close(
-            ret_np=frontend_u[...,:frontend_s.shape[0]] @ np.diag(frontend_s) @ frontend_vh,
-            ret_from_gt_np=u[...,:s.shape[0]] @ np.diag(s) @ vh,
+            ret_np=frontend_u[..., : frontend_s.shape[0]]
+            @ np.diag(frontend_s)
+            @ frontend_vh,
+            ret_from_gt_np=u[..., : s.shape[0]] @ np.diag(s) @ vh,
             atol=1e-04,
             backend=backend_fw,
             ground_truth_backend=frontend,
@@ -1308,7 +1312,6 @@ def test_torch_svd(
         )
 
 
-
 # svdvals
 @handle_frontend_test(
     fn_tree="torch.linalg.svdvals",

From c1a6632bfd62c3c8f1b88cf306ade754082b1a1d Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Thu, 22 Aug 2024 03:43:22 +0000
Subject: [PATCH 26/35] changed
 ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py::test_torch_svd
 so that complex number inputs are also tested, they are passing

---
 .../frontends/torch/blas_and_lapack_ops.py         | 14 +++++++++++---
 .../test_torch/test_blas_and_lapack_ops.py         |  4 +++-
 2 files changed, 14 insertions(+), 4 deletions(-)

diff --git a/ivy/functional/frontends/torch/blas_and_lapack_ops.py b/ivy/functional/frontends/torch/blas_and_lapack_ops.py
index 4ced2b61b24e8..f5f33ec714b74 100644
--- a/ivy/functional/frontends/torch/blas_and_lapack_ops.py
+++ b/ivy/functional/frontends/torch/blas_and_lapack_ops.py
@@ -1,6 +1,6 @@
 # global
 import ivy
-from ivy.func_wrapper import with_unsupported_dtypes
+from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
 import ivy.functional.frontends.torch as torch_frontend
 from collections import namedtuple
 from ivy.functional.frontends.torch.func_wrapper import to_ivy_arrays_and_back
@@ -190,10 +190,14 @@ def slogdet(A, *, out=None):
     return torch_frontend.linalg.slogdet(A, out=out)
 
 
+@with_supported_dtypes(
+    {"2.15.0 and below": ("float64", "float32", "half", "complex64", "complex128")},
+    "torch",
+)
 @to_ivy_arrays_and_back
 def svd(input, some=True, compute_uv=True, *, out=None):
     retu = ivy.svd(input, full_matrices=not some, compute_uv=compute_uv)
-    results = namedtuple("svd", 'U S V')
+    results = namedtuple("svd", "U S V")
     if compute_uv:
         ret = results(retu[0], retu[1], ivy.adjoint(retu[2]))
     else:
@@ -202,7 +206,11 @@ def svd(input, some=True, compute_uv=True, *, out=None):
         shape2 = shape
         shape1[-2] = shape[-1]
         shape2[-1] = shape[-2]
-        ret = results(ivy.zeros(shape1, device=input.device, dtype=input.dtype), ivy.astype(retu[0], input.dtype), ivy.zeros(shape2, device=input.device, dtype=input.dtype))
+        ret = results(
+            ivy.zeros(shape1, device=input.device, dtype=input.dtype),
+            ivy.astype(retu[0], input.dtype),
+            ivy.zeros(shape2, device=input.device, dtype=input.dtype),
+        )
     if ivy.exists(out):
         return ivy.inplace_update(out, ret)
     return ret
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
index a9580069cb512..31bfd26582d55 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
@@ -886,7 +886,9 @@ def test_torch_svd(
         frontend_ret = [x.detach() for x in frontend_ret]
         ret = [x.detach() for x in ret]
     ret = [np.asarray(x) for x in ret]
-    frontend_ret = [np.asarray(x).astype(input_dtype[0]) for x in frontend_ret]
+    frontend_ret = [
+        np.asarray(x.resolve_conj()).astype(input_dtype[0]) for x in frontend_ret
+    ]
     u, s, v = ret
     frontend_u, frontend_s, frontend_v = frontend_ret
     if not compute_uv:

From 9b75cd11f201836111bfa08f3ee67d4488fb575e Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Thu, 22 Aug 2024 05:54:41 +0000
Subject: [PATCH 27/35] changed all the torch's test_torch_svd so that complex
 number inputs are also tested, they are all passing

---
 ivy/functional/frontends/torch/blas_and_lapack_ops.py       | 3 +--
 ivy/functional/frontends/torch/tensor.py                    | 4 +++-
 ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py | 2 +-
 ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py | 6 ++++--
 4 files changed, 9 insertions(+), 6 deletions(-)

diff --git a/ivy/functional/frontends/torch/blas_and_lapack_ops.py b/ivy/functional/frontends/torch/blas_and_lapack_ops.py
index f5f33ec714b74..403175a8253a6 100644
--- a/ivy/functional/frontends/torch/blas_and_lapack_ops.py
+++ b/ivy/functional/frontends/torch/blas_and_lapack_ops.py
@@ -191,8 +191,7 @@ def slogdet(A, *, out=None):
 
 
 @with_supported_dtypes(
-    {"2.15.0 and below": ("float64", "float32", "half", "complex64", "complex128")},
-    "torch",
+    {"2.2 and below": ("float32", "float64", "complex32", "complex64")}, "torch"
 )
 @to_ivy_arrays_and_back
 def svd(input, some=True, compute_uv=True, *, out=None):
diff --git a/ivy/functional/frontends/torch/tensor.py b/ivy/functional/frontends/torch/tensor.py
index d27360e361468..6cdca52182b4c 100644
--- a/ivy/functional/frontends/torch/tensor.py
+++ b/ivy/functional/frontends/torch/tensor.py
@@ -2009,7 +2009,9 @@ def adjoint(self):
     def conj(self):
         return torch_frontend.conj(self)
 
-    @with_unsupported_dtypes({"2.2 and below": ("float16", "bfloat16")}, "torch")
+    @with_supported_dtypes(
+        {"2.2 and below": ("float32", "float64", "complex32", "complex64")}, "torch"
+    )
     def svd(self, some=True, compute_uv=True, *, out=None):
         return torch_frontend.svd(self, some=some, compute_uv=compute_uv, out=out)
 
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
index 6884f2864148a..0c908db303618 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
@@ -1249,7 +1249,7 @@ def test_torch_solve_ex(
 @handle_frontend_test(
     fn_tree="torch.linalg.svd",
     dtype_and_x=helpers.dtype_and_values(
-        available_dtypes=helpers.get_dtypes("float"),
+        available_dtypes=helpers.get_dtypes("valid"),
         min_value=0,
         max_value=10,
         shape=helpers.ints(min_value=2, max_value=5).map(lambda x: (x, x)),
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
index 0640f82060abc..2d6c53b093212 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
@@ -13144,13 +13144,15 @@ def test_torch_svd(
         test_values=False,
     )
     ret = [np.asarray(x) for x in ret]
-    frontend_ret = [np.asarray(x) for x in frontend_ret]
+    frontend_ret = [np.asarray(x.resolve_conj()) for x in frontend_ret]
 
     u, s, v = ret
     frontend_u, frontend_s, frontend_v = frontend_ret
     if not compute_uv:
         helpers.assert_all_close(
-            ret_np=frontend_s,
+            ret_np=frontend_s.astype(
+                input_dtype[0]
+            ),  # it somehow always return float32
             ret_from_gt_np=s,
             atol=1e-04,
             backend=backend_fw,

From 5c9de15b384b68a4208e28f749c08e03ea6b24b2 Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Thu, 22 Aug 2024 07:00:24 +0000
Subject: [PATCH 28/35] try to update torch and tensorflow's svd functions as
 they somehow return fixed dtypes depending on if input is complex,

---
 ivy/functional/frontends/tensorflow/linalg.py | 14 +++++++++--
 ivy/functional/frontends/torch/linalg.py      |  8 ++++++-
 .../test_tensorflow/test_linalg.py            |  2 +-
 .../test_frontends/test_torch/test_linalg.py  | 24 +++++++++++--------
 4 files changed, 34 insertions(+), 14 deletions(-)

diff --git a/ivy/functional/frontends/tensorflow/linalg.py b/ivy/functional/frontends/tensorflow/linalg.py
index fe797894f4aef..7b2197111f3f6 100644
--- a/ivy/functional/frontends/tensorflow/linalg.py
+++ b/ivy/functional/frontends/tensorflow/linalg.py
@@ -357,13 +357,23 @@ def solve(matrix, rhs, /, *, adjoint=False, name=None):
 
 
 @to_ivy_arrays_and_back
+@with_supported_dtypes(
+    {"2.15.0 and below": ("float32", "float64", "half", "complex32", "complex64")},
+    "tensorflow",
+)
 def svd(a, /, *, full_matrices=False, compute_uv=True, name=None):
+    if ivy.is_complex_dtype(a.dtype):
+        d = ivy.complex128
+    else:
+        d = ivy.float64
     if compute_uv:
         svd = ivy.svd(a, compute_uv=compute_uv, full_matrices=full_matrices)
-        return tuple([ivy.astype(svd.S, ivy.float64), ivy.astype(svd.U, ivy.float64), ivy.astype(svd.Vh.T, ivy.float64)])
+        return tuple(
+            [ivy.astype(svd.S, d), ivy.astype(svd.U, d), ivy.astype(svd.Vh.T, d)]
+        )
     else:
         svd = ivy.svd(a, compute_uv=compute_uv, full_matrices=full_matrices)
-        return ivy.astype(svd.S, ivy.float64)
+        return ivy.astype(svd.S, d)
 
 
 @to_ivy_arrays_and_back
diff --git a/ivy/functional/frontends/torch/linalg.py b/ivy/functional/frontends/torch/linalg.py
index e52d69a0de8c8..39a58e868b16e 100644
--- a/ivy/functional/frontends/torch/linalg.py
+++ b/ivy/functional/frontends/torch/linalg.py
@@ -333,7 +333,13 @@ def solve_ex(A, B, *, left=True, check_errors=False, out=None):
 )
 def svd(A, /, *, full_matrices=True, driver=None, out=None):
     # TODO: add handling for driver
-    ret = ivy.svd(A, compute_uv=True, full_matrices=full_matrices)
+    USVh = ivy.svd(A, compute_uv=True, full_matrices=full_matrices)
+    if ivy.is_complex_dtype(A.dtype):
+        d = ivy.complex64
+    else:
+        d = ivy.float32
+    nt = namedtuple("svd", "U S Vh")
+    ret = nt(ivy.astype(USVh.U, d), ivy.astype(USVh.S, d), ivy.astype(USVh.Vh, d))
     if ivy.exists(out):
         return ivy.inplace_update(out, ret)
     return ret
diff --git a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_linalg.py
index c6a62f6598367..1f33ca53cc80f 100644
--- a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_linalg.py
@@ -1074,7 +1074,7 @@ def test_tensorflow_solve(
 @handle_frontend_test(
     fn_tree="tensorflow.linalg.svd",
     dtype_and_x=helpers.dtype_and_values(
-        available_dtypes=helpers.get_dtypes("float"),
+        available_dtypes=helpers.get_dtypes("valid"),
         min_value=0,
         max_value=10,
         shape=helpers.ints(min_value=2, max_value=5).map(lambda x: (x, x)),
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
index 0c908db303618..51a73184aee96 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
@@ -1284,19 +1284,23 @@ def test_torch_svd(
     if backend_fw == "torch":
         frontend_ret = [x.detach() for x in frontend_ret]
         ret = [x.detach() for x in ret]
-        ret = [np.asarray(x, dtype=np.dtype(getattr(np, dtype[0]))) for x in ret]
-    else:
-        ret = [np.asarray(x) for x in ret]
-    frontend_ret = [
-        np.asarray(x, dtype=np.dtype(getattr(np, dtype[0]))) for x in frontend_ret
-    ]
+    ret = [np.asarray(x) for x in ret]
+    frontend_ret = [np.asarray(x) for x in frontend_ret]
     u, s, vh = ret
     frontend_u, frontend_s, frontend_vh = frontend_ret
+    if ivy.is_complex_dtype(x.dtype):
+        d = ivy.complex64
+    else:
+        d = ivy.float32
+    # the dtypes somehow become wrong after matrix calculation
+    # though the return values should have correct dtypes
     if full_matrices:
         helpers.assert_all_close(
-            ret_np=frontend_u[..., : frontend_s.shape[0]]
-            @ np.diag(frontend_s)
-            @ frontend_vh,
+            ret_np=(
+                frontend_u[..., : frontend_s.shape[0]]
+                @ np.diag(frontend_s)
+                @ frontend_vh
+            ).astype(d),
             ret_from_gt_np=u[..., : s.shape[0]] @ np.diag(s) @ vh,
             atol=1e-04,
             backend=backend_fw,
@@ -1304,7 +1308,7 @@ def test_torch_svd(
         )
     else:
         helpers.assert_all_close(
-            ret_np=frontend_u @ np.diag(frontend_s) @ frontend_vh,
+            ret_np=(frontend_u @ np.diag(frontend_s) @ frontend_vh).astype(d),
             ret_from_gt_np=u @ np.diag(s) @ vh,
             atol=1e-04,
             backend=backend_fw,

From 2f76f664e300625f8d822164eecdc61f657953b7 Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Thu, 22 Aug 2024 09:51:42 +0000
Subject: [PATCH 29/35] seems like should not use svdvals as it always return a
 not complex value instead as the same as the input, but the documents shows
 that the S component will always be real, which is different from the
 groundtruth behavior shown in the, updated the jax svd tests to check for
 complex inputs

---
 ivy/functional/frontends/jax/lax/linalg.py                 | 6 +++---
 ivy/functional/frontends/numpy/linalg/decompositions.py    | 7 ++++++-
 .../test_frontends/test_jax/test_lax/test_linalg.py        | 2 +-
 .../test_frontends/test_jax/test_numpy/test_linalg.py      | 4 ++--
 .../test_numpy/test_linalg/test_decompositions.py          | 4 ++--
 5 files changed, 14 insertions(+), 9 deletions(-)

diff --git a/ivy/functional/frontends/jax/lax/linalg.py b/ivy/functional/frontends/jax/lax/linalg.py
index d48cac8a85911..7180ae2d1a988 100644
--- a/ivy/functional/frontends/jax/lax/linalg.py
+++ b/ivy/functional/frontends/jax/lax/linalg.py
@@ -46,9 +46,9 @@ def qr(x, /, *, full_matrices=False):
 @to_ivy_arrays_and_back
 @with_unsupported_dtypes({"0.4.14 and below": ("bfloat16",)}, "jax")
 def svd(x, /, *, full_matrices=True, compute_uv=True, subset_by_index=None):
-    #TODO: handle subset_by_index
+    # TODO: handle subset_by_index
+    ret = ivy.svd(x, full_matrices=full_matrices)
     if compute_uv:
-        return tuple(ivy.svd(x, full_matrices=full_matrices))
+        return tuple(ret)
     else:
         return ivy.svdvals(x)
-
diff --git a/ivy/functional/frontends/numpy/linalg/decompositions.py b/ivy/functional/frontends/numpy/linalg/decompositions.py
index 927096f08476a..5fe8c364e0f27 100644
--- a/ivy/functional/frontends/numpy/linalg/decompositions.py
+++ b/ivy/functional/frontends/numpy/linalg/decompositions.py
@@ -1,6 +1,7 @@
 # local
 import ivy
 from ivy.functional.frontends.numpy.func_wrapper import to_ivy_arrays_and_back
+from ivy.func_wrapper import with_supported_dtypes
 
 
 @to_ivy_arrays_and_back
@@ -14,8 +15,12 @@ def qr(a, mode="reduced"):
 
 
 @to_ivy_arrays_and_back
+@with_supported_dtypes(
+    {"1.26.3 and below": ("float64", "float32", "half", "complex64", "complex128")},
+    "numpy",
+)
 def svd(a, full_matrices=True, compute_uv=True, hermitian=False):
-    # Todo: hermitian handling, ivy.astype does not work for some reason
+    # Todo: hermitian handling
     if compute_uv:
         return ivy.svd(a, full_matrices=full_matrices, compute_uv=compute_uv)
     else:
diff --git a/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
index d25a5ec3858f2..0698b1ff9cdbe 100644
--- a/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
@@ -164,7 +164,7 @@ def test_jax_qr(
 @handle_frontend_test(
     fn_tree="jax.lax.linalg.svd",
     dtype_x=helpers.dtype_and_values(
-        available_dtypes=helpers.get_dtypes("float"),
+        available_dtypes=helpers.get_dtypes("valid"),
         min_value=0,
         max_value=10,
         shape=helpers.ints(min_value=2, max_value=5).map(lambda x: (x, x)),
diff --git a/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py
index ea390e6526aed..6cf1376c6bccf 100644
--- a/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py
@@ -854,11 +854,11 @@ def test_jax_solve(
 @handle_frontend_test(
     fn_tree="jax.numpy.linalg.svd",
     dtype_and_x=helpers.dtype_and_values(
-        available_dtypes=helpers.get_dtypes("float"),
+        available_dtypes=helpers.get_dtypes("valid"),
         min_value=0,
         max_value=10,
         shape=helpers.ints(min_value=2, max_value=5).map(lambda x: (x, x)),
-    ).filter(lambda x: "float16" not in x[0] and "bfloat16" not in x[0]),
+    ),
     full_matrices=st.booleans(),
     compute_uv=st.booleans(),
     test_with_out=st.just(False),
diff --git a/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py b/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py
index 1e43a8a4e866c..a8d57e1100b1b 100644
--- a/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py
+++ b/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_decompositions.py
@@ -122,7 +122,7 @@ def test_numpy_svd(
     )
     if compute_uv:
         ret = [np.asarray(x) for x in ret]
-        frontend_ret = [np.asarray(x).astype(dtype[0]) for x in frontend_ret]
+        frontend_ret = [np.asarray(x) for x in frontend_ret]
         u, s, vh = ret
         frontend_u, frontend_s, frontend_vh = frontend_ret
         if not full_matrices:
@@ -145,7 +145,7 @@ def test_numpy_svd(
             )
     else:
         helpers.assert_all_close(
-            ret_np=frontend_ret.astype(dtype[0]),
+            ret_np=frontend_ret,
             ret_from_gt_np=ret,
             atol=1e-3,
             backend=backend_fw,

From 412e60c8b75348fec397867e5abef0598b5e7f57 Mon Sep 17 00:00:00 2001
From: Jin Wang <jin.wang-12@student.manchester.ac.uk>
Date: Fri, 23 Aug 2024 08:08:14 +0000
Subject: [PATCH 30/35] fixed jax's svd to teat for complex input. though only
 jax.lax.linalg.svd fail for tensorflow backend due to significant and updated
 all relavent svd with more complex supported dtype

---
 ivy/functional/frontends/jax/lax/linalg.py    | 28 +++++++++++++++----
 ivy/functional/frontends/jax/numpy/linalg.py  | 26 ++++++++++++++---
 .../frontends/numpy/linalg/decompositions.py  | 11 +++++++-
 ivy/functional/frontends/tensorflow/linalg.py | 11 +++++++-
 .../frontends/tensorflow/raw_ops.py           | 11 +++++++-
 .../frontends/torch/blas_and_lapack_ops.py    | 12 +++++++-
 ivy/functional/frontends/torch/linalg.py      | 12 +++++++-
 ivy/functional/frontends/torch/tensor.py      | 12 +++++++-
 .../test_jax/test_lax/test_linalg.py          |  6 ++--
 .../test_jax/test_numpy/test_linalg.py        |  7 ++---
 10 files changed, 113 insertions(+), 23 deletions(-)

diff --git a/ivy/functional/frontends/jax/lax/linalg.py b/ivy/functional/frontends/jax/lax/linalg.py
index 7180ae2d1a988..c9568fbfdf214 100644
--- a/ivy/functional/frontends/jax/lax/linalg.py
+++ b/ivy/functional/frontends/jax/lax/linalg.py
@@ -1,6 +1,6 @@
 import ivy
 from ivy.functional.frontends.jax.func_wrapper import to_ivy_arrays_and_back
-from ivy.func_wrapper import with_unsupported_dtypes
+from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
 
 
 @to_ivy_arrays_and_back
@@ -44,11 +44,29 @@ def qr(x, /, *, full_matrices=False):
 
 
 @to_ivy_arrays_and_back
-@with_unsupported_dtypes({"0.4.14 and below": ("bfloat16",)}, "jax")
+@with_supported_dtypes(
+    {
+        "0.4.14 and below": (
+            "float64",
+            "float32",
+            "half",
+            "complex32",
+            "complex64",
+            "complex128",
+        )
+    },
+    "jax",
+)
 def svd(x, /, *, full_matrices=True, compute_uv=True, subset_by_index=None):
     # TODO: handle subset_by_index
-    ret = ivy.svd(x, full_matrices=full_matrices)
+    if ivy.is_complex_dtype(x.dtype):
+        d = ivy.complex128
+    else:
+        d = ivy.float64
     if compute_uv:
-        return tuple(ret)
+        svd = ivy.svd(x, compute_uv=compute_uv, full_matrices=full_matrices)
+        return tuple(
+            [ivy.astype(svd.U, d), ivy.astype(svd.S, d), ivy.astype(svd.Vh, d)]
+        )
     else:
-        return ivy.svdvals(x)
+        return ivy.astype(ivy.svdvals(x), ivy.float64)
diff --git a/ivy/functional/frontends/jax/numpy/linalg.py b/ivy/functional/frontends/jax/numpy/linalg.py
index 993d8a8328cee..1265b6648246c 100644
--- a/ivy/functional/frontends/jax/numpy/linalg.py
+++ b/ivy/functional/frontends/jax/numpy/linalg.py
@@ -120,14 +120,32 @@ def solve(a, b):
 
 
 @to_ivy_arrays_and_back
-@with_unsupported_dtypes({"0.4.24 and below": ("float16", "bfloat16")}, "jax")
+@with_supported_dtypes(
+    {
+        "0.4.24 and below": (
+            "float64",
+            "float32",
+            "half",
+            "complex32",
+            "complex64",
+            "complex128",
+        )
+    },
+    "jax",
+)
 def svd(a, /, *, full_matrices=True, compute_uv=True, hermitian=None):
     # TODO: handle hermitian
-    ret = ivy.svd(a, full_matrices=full_matrices, compute_uv=compute_uv)
+    if ivy.is_complex_dtype(a.dtype):
+        d = ivy.complex128
+    else:
+        d = ivy.float64
     if compute_uv:
-        return tuple(ret)
+        svd = ivy.svd(a, compute_uv=compute_uv, full_matrices=full_matrices)
+        return tuple(
+            [ivy.astype(svd.U, d), ivy.astype(svd.S, d), ivy.astype(svd.Vh, d)]
+        )
     else:
-        return ivy.svdvals(a)
+        return ivy.astype(ivy.svdvals(a), ivy.float64)
 
 
 @to_ivy_arrays_and_back
diff --git a/ivy/functional/frontends/numpy/linalg/decompositions.py b/ivy/functional/frontends/numpy/linalg/decompositions.py
index 5fe8c364e0f27..7147c7d1e6679 100644
--- a/ivy/functional/frontends/numpy/linalg/decompositions.py
+++ b/ivy/functional/frontends/numpy/linalg/decompositions.py
@@ -16,7 +16,16 @@ def qr(a, mode="reduced"):
 
 @to_ivy_arrays_and_back
 @with_supported_dtypes(
-    {"1.26.3 and below": ("float64", "float32", "half", "complex64", "complex128")},
+    {
+        "1.26.3 and below": (
+            "float64",
+            "float32",
+            "half",
+            "complex32",
+            "complex64",
+            "complex128",
+        )
+    },
     "numpy",
 )
 def svd(a, full_matrices=True, compute_uv=True, hermitian=False):
diff --git a/ivy/functional/frontends/tensorflow/linalg.py b/ivy/functional/frontends/tensorflow/linalg.py
index 7b2197111f3f6..7d80146b349b3 100644
--- a/ivy/functional/frontends/tensorflow/linalg.py
+++ b/ivy/functional/frontends/tensorflow/linalg.py
@@ -358,7 +358,16 @@ def solve(matrix, rhs, /, *, adjoint=False, name=None):
 
 @to_ivy_arrays_and_back
 @with_supported_dtypes(
-    {"2.15.0 and below": ("float32", "float64", "half", "complex32", "complex64")},
+    {
+        "2.15.0 and below": (
+            "float32",
+            "float64",
+            "half",
+            "complex32",
+            "complex64",
+            "complex128",
+        )
+    },
     "tensorflow",
 )
 def svd(a, /, *, full_matrices=False, compute_uv=True, name=None):
diff --git a/ivy/functional/frontends/tensorflow/raw_ops.py b/ivy/functional/frontends/tensorflow/raw_ops.py
index 0128e89695fca..38ffbcd15b160 100644
--- a/ivy/functional/frontends/tensorflow/raw_ops.py
+++ b/ivy/functional/frontends/tensorflow/raw_ops.py
@@ -832,7 +832,16 @@ def Sum(*, input, axis, keep_dims=False, name="Sum"):
 
 
 @with_supported_dtypes(
-    {"2.15.0 and below": ("float64", "float32", "half", "complex64", "complex128")},
+    {
+        "2.15.0 and below": (
+            "float64",
+            "float32",
+            "half",
+            "complex32",
+            "complex64",
+            "complex128",
+        )
+    },
     "tensorflow",
 )
 @to_ivy_arrays_and_back
diff --git a/ivy/functional/frontends/torch/blas_and_lapack_ops.py b/ivy/functional/frontends/torch/blas_and_lapack_ops.py
index 403175a8253a6..c0f6f27bd584b 100644
--- a/ivy/functional/frontends/torch/blas_and_lapack_ops.py
+++ b/ivy/functional/frontends/torch/blas_and_lapack_ops.py
@@ -191,7 +191,17 @@ def slogdet(A, *, out=None):
 
 
 @with_supported_dtypes(
-    {"2.2 and below": ("float32", "float64", "complex32", "complex64")}, "torch"
+    {
+        "2.2 and below": (
+            "float64",
+            "float32",
+            "half",
+            "complex32",
+            "complex64",
+            "complex128",
+        )
+    },
+    "torch",
 )
 @to_ivy_arrays_and_back
 def svd(input, some=True, compute_uv=True, *, out=None):
diff --git a/ivy/functional/frontends/torch/linalg.py b/ivy/functional/frontends/torch/linalg.py
index 39a58e868b16e..79ac5f318f20c 100644
--- a/ivy/functional/frontends/torch/linalg.py
+++ b/ivy/functional/frontends/torch/linalg.py
@@ -329,7 +329,17 @@ def solve_ex(A, B, *, left=True, check_errors=False, out=None):
 
 @to_ivy_arrays_and_back
 @with_supported_dtypes(
-    {"2.2 and below": ("float32", "float64", "complex32", "complex64")}, "torch"
+    {
+        "2.2 and below": (
+            "float64",
+            "float32",
+            "half",
+            "complex32",
+            "complex64",
+            "complex128",
+        )
+    },
+    "torch",
 )
 def svd(A, /, *, full_matrices=True, driver=None, out=None):
     # TODO: add handling for driver
diff --git a/ivy/functional/frontends/torch/tensor.py b/ivy/functional/frontends/torch/tensor.py
index 6cdca52182b4c..ea51c564388e9 100644
--- a/ivy/functional/frontends/torch/tensor.py
+++ b/ivy/functional/frontends/torch/tensor.py
@@ -2010,7 +2010,17 @@ def conj(self):
         return torch_frontend.conj(self)
 
     @with_supported_dtypes(
-        {"2.2 and below": ("float32", "float64", "complex32", "complex64")}, "torch"
+        {
+            "2.2 and below": (
+                "float64",
+                "float32",
+                "half",
+                "complex32",
+                "complex64",
+                "complex128",
+            )
+        },
+        "torch",
     )
     def svd(self, some=True, compute_uv=True, *, out=None):
         return torch_frontend.svd(self, some=some, compute_uv=compute_uv, out=out)
diff --git a/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
index 0698b1ff9cdbe..dae44990b5a34 100644
--- a/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_jax/test_lax/test_linalg.py
@@ -211,7 +211,7 @@ def test_jax_svd(
         if backend_fw == "torch":
             ret = ret.detach()
         assert_all_close(
-            ret_np=np.asarray(frontend_ret, dtype=np.dtype(getattr(np, dtype[0]))),
+            ret_np=np.asarray(frontend_ret),
             ret_from_gt_np=np.asarray(ret),
             rtol=1e-3,
             backend=backend_fw,
@@ -221,9 +221,7 @@ def test_jax_svd(
         if backend_fw == "torch":
             ret = [x.detach() for x in ret]
         ret = [np.asarray(x) for x in ret]
-        frontend_ret = [
-            np.asarray(x, dtype=np.dtype(getattr(np, dtype[0]))) for x in frontend_ret
-        ]
+        frontend_ret = [np.asarray(x) for x in frontend_ret]
         u, s, v = ret
         frontend_u, frontend_s, frontend_v = frontend_ret
         if not full_matrices:
diff --git a/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py
index 6cf1376c6bccf..aee40b5b147fa 100644
--- a/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_linalg.py
@@ -896,9 +896,8 @@ def test_jax_svd(
                 x for x in frontend_ret
             ]  # unpack jaxlib.xla_extension.ArrayImpl as it is no .detach()
             ret = [x for x in frontend_ret]
-        detyp = np.dtype(getattr(np, dtype[0]))
-        ret = [np.asarray(x).astype(detyp) for x in ret]
-        frontend_ret = [np.asarray(x, dtype=detyp) for x in frontend_ret]
+        ret = [np.asarray(x) for x in ret]
+        frontend_ret = [np.asarray(x) for x in frontend_ret]
         u, s, vh = ret
         frontend_u, frontend_s, frontend_vh = frontend_ret
         if not full_matrices:
@@ -923,7 +922,7 @@ def test_jax_svd(
         if backend_fw == "torch":
             ret = ret.detach()
         assert_all_close(
-            ret_np=np.asarray(frontend_ret, dtype=np.dtype(getattr(np, dtype[0]))),
+            ret_np=np.asarray(frontend_ret),
             ret_from_gt_np=np.asarray(ret),
             atol=1e-3,
             backend=backend_fw,

From 99b7266f884277d0c4b641bcf095be51eff82518 Mon Sep 17 00:00:00 2001
From: Daniel4078 <45633544+Daniel4078@users.noreply.github.com>
Date: Sat, 28 Sep 2024 20:40:29 +0100
Subject: [PATCH 31/35] small update on test_torch.test_tensor.test_torch_svd

---
 ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py | 5 +----
 1 file changed, 1 insertion(+), 4 deletions(-)

diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
index 2d6c53b093212..887f2cbfdab4d 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
@@ -13145,14 +13145,11 @@ def test_torch_svd(
     )
     ret = [np.asarray(x) for x in ret]
     frontend_ret = [np.asarray(x.resolve_conj()) for x in frontend_ret]
-
     u, s, v = ret
     frontend_u, frontend_s, frontend_v = frontend_ret
     if not compute_uv:
         helpers.assert_all_close(
-            ret_np=frontend_s.astype(
-                input_dtype[0]
-            ),  # it somehow always return float32
+            ret_np=frontend_s
             ret_from_gt_np=s,
             atol=1e-04,
             backend=backend_fw,

From 00f7754a90007dcf86997b2c55f5bb49158c1bb7 Mon Sep 17 00:00:00 2001
From: Daniel4078 <45633544+Daniel4078@users.noreply.github.com>
Date: Sat, 28 Sep 2024 20:42:54 +0100
Subject: [PATCH 32/35] Update test_blas_and_lapack_ops.py

---
 .../test_frontends/test_torch/test_blas_and_lapack_ops.py     | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
index 31bfd26582d55..8cd18e858f16e 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_blas_and_lapack_ops.py
@@ -886,9 +886,7 @@ def test_torch_svd(
         frontend_ret = [x.detach() for x in frontend_ret]
         ret = [x.detach() for x in ret]
     ret = [np.asarray(x) for x in ret]
-    frontend_ret = [
-        np.asarray(x.resolve_conj()).astype(input_dtype[0]) for x in frontend_ret
-    ]
+    frontend_ret = [np.asarray(x.resolve_conj()) for x in frontend_ret]
     u, s, v = ret
     frontend_u, frontend_s, frontend_v = frontend_ret
     if not compute_uv:

From 49db616fa28068b9387e2012e65c8b9262d94ed2 Mon Sep 17 00:00:00 2001
From: Daniel4078 <45633544+Daniel4078@users.noreply.github.com>
Date: Sat, 28 Sep 2024 20:45:02 +0100
Subject: [PATCH 33/35] Update test_linalg.py

---
 .../test_ivy/test_frontends/test_torch/test_linalg.py  | 10 ++--------
 1 file changed, 2 insertions(+), 8 deletions(-)

diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
index ee79e451aefe5..0739426396286 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
@@ -1282,19 +1282,13 @@ def test_torch_svd(
     frontend_ret = [np.asarray(x) for x in frontend_ret]
     u, s, vh = ret
     frontend_u, frontend_s, frontend_vh = frontend_ret
-    if ivy.is_complex_dtype(x.dtype):
-        d = ivy.complex64
-    else:
-        d = ivy.float32
-    # the dtypes somehow become wrong after matrix calculation
-    # though the return values should have correct dtypes
     if full_matrices:
         helpers.assert_all_close(
             ret_np=(
                 frontend_u[..., : frontend_s.shape[0]]
                 @ np.diag(frontend_s)
                 @ frontend_vh
-            ).astype(d),
+            )
             ret_from_gt_np=u[..., : s.shape[0]] @ np.diag(s) @ vh,
             atol=1e-04,
             backend=backend_fw,
@@ -1302,7 +1296,7 @@ def test_torch_svd(
         )
     else:
         helpers.assert_all_close(
-            ret_np=(frontend_u @ np.diag(frontend_s) @ frontend_vh).astype(d),
+            ret_np=(frontend_u @ np.diag(frontend_s) @ frontend_vh),
             ret_from_gt_np=u @ np.diag(s) @ vh,
             atol=1e-04,
             backend=backend_fw,

From 637652ef54cca5f38a5508e94195e4b570551693 Mon Sep 17 00:00:00 2001
From: Daniel4078 <45633544+Daniel4078@users.noreply.github.com>
Date: Mon, 30 Sep 2024 10:43:44 +0100
Subject: [PATCH 34/35] Update test_linalg.py

---
 ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
index 0739426396286..6710067a2678e 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
@@ -1288,7 +1288,7 @@ def test_torch_svd(
                 frontend_u[..., : frontend_s.shape[0]]
                 @ np.diag(frontend_s)
                 @ frontend_vh
-            )
+            ),
             ret_from_gt_np=u[..., : s.shape[0]] @ np.diag(s) @ vh,
             atol=1e-04,
             backend=backend_fw,

From 390b00bb5c403ce4fa2d16ebc3fd09e01f2fb7b8 Mon Sep 17 00:00:00 2001
From: Daniel4078 <45633544+Daniel4078@users.noreply.github.com>
Date: Mon, 30 Sep 2024 10:45:11 +0100
Subject: [PATCH 35/35] Update test_tensor.py

---
 ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
index 887f2cbfdab4d..eaad5586b17fd 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
@@ -13149,7 +13149,7 @@ def test_torch_svd(
     frontend_u, frontend_s, frontend_v = frontend_ret
     if not compute_uv:
         helpers.assert_all_close(
-            ret_np=frontend_s
+            ret_np=frontend_s,
             ret_from_gt_np=s,
             atol=1e-04,
             backend=backend_fw,