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fix: Issue with unsupported dtypes #27934

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merged 2 commits into from
Jan 17, 2024
Merged

fix: Issue with unsupported dtypes #27934

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5c3aeae
fix: fixed an issue with _nested_get that was failing the unsupported…
vedpatwardhan Jan 17, 2024
f3f27f1
also updated import name in torch.nn
vedpatwardhan Jan 17, 2024
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9 changes: 5 additions & 4 deletions ivy/functional/frontends/torch/tensor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,6 @@
# local
import ivy
import ivy.functional.frontends.torch as torch_frontend
import ivy.functional.frontends.torch.nn.functional as torch_frontend_nn
from ivy.functional.frontends.numpy.creation_routines.from_existing_data import (
array as np_frontend_array,
)
Expand Down Expand Up @@ -390,7 +389,7 @@ def log2(self):

@with_unsupported_dtypes({"2.1.2 and below": ("float16", "bfloat16")}, "torch")
def relu(self):
return torch_frontend_nn.relu(self)
return torch_frontend.nn.functional.relu(self)

@numpy_to_torch_style_args
@with_unsupported_dtypes({"2.1.2 and below": ("complex",)}, "torch")
Expand Down Expand Up @@ -1711,12 +1710,14 @@ def stride(self, dim=None):
)
def log1p(self):
promoted_type = ivy.promote_types(self.dtype, "float32")
return torch_frontend.log1p(self).to(promoted_type)
res = torch_frontend.log1p(self)
return res.to(promoted_type)

@with_supported_dtypes({"2.1.2 and below": ("float32", "float64")}, "torch")
def log1p_(self):
promoted_type = ivy.promote_types(self.dtype, "float32")
self.ivy_array = torch_frontend.log1p(self).to(promoted_type).ivy_array
res = torch_frontend.log1p(self)
self.ivy_array = res.to(promoted_type).ivy_array
return self

def baddbmm(self, batch1, batch2, *, beta=1, alpha=1):
Expand Down
15 changes: 7 additions & 8 deletions ivy/functional/ivy/data_type.py
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Original file line number Diff line number Diff line change
Expand Up @@ -188,16 +188,15 @@ def _nested_get(f, base_set, merge_fn, get_fn, wrapper=set):
}
for key in fl:
if "frontend" in key:
fn_tree = key.split(".")
root, tree, fn_name = fn_tree[0], fn_tree[1:-1], fn_tree[-1]
root_module = importlib.import_module(
".".join([frontends[root], *tree])
)
frontend_fn = getattr(root_module, fn_name)
frontend_fl = _get_function_list(frontend_fn)
frontend_fn = fl[key]
for frontend in frontends:
if frontend in key:
key = key.replace(frontend, frontends[frontend])
frontend_module = ".".join(key.split(".")[:-1])
frontend_fl = {key: frontend_fn}
res += list(
_get_functions_from_string(
frontend_fl, __import__(frontend_fn.__module__)
frontend_fl, importlib.import_module(frontend_module)
)
)
to_visit.extend(set(res))
Expand Down
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