Added Max Pool 3D to Paddle pooling.py

ivy/functional/frontends/paddle/nn/functional/pooling.py

@@ -113,3 +113,39 @@ def max_unpool1d(
     name=None,
 ):
     return ivy.max_unpool1d(x, indices, kernel_size, stride, padding, data_format)
+
+
+@to_ivy_arrays_and_back
+@with_supported_dtypes({"2.5.1 and below": ("float32", "float64")}, "paddle")
+def max_pool3d(
+     x,
+     kernel_size,
+     stride=None,
+     padding=0,
+     return_mask=False,
+     ceil_mode=False,
+     data_format='NCDHW',
+     name=None
+):
+    if stride is None:
+        stride = kernel_size
+    kernel_size = _broadcast_pooling_helper(kernel_size, "3d", name="kernel_size")
+    padding = _broadcast_pooling_helper(padding, "3d", name="padding")
+    # Figure out padding string
+    if all(
+        [pad == ivy.ceil((kernel - 1) / 2) for kernel, pad in zip(kernel_size, padding)]
+    ):
+        padding = "SAME"
+    else:
+        padding = "VALID"
+
+
+     return ivy.max_pool3d(
+         x,
+         kernel_size,
+         stride,
+         padding,
+         return_mask=return_mask,
+         ceil_mode=ceil_mode,
+         data_format=data_format
+    )

ivy_tests/test_ivy/test_frontends/test_paddle/test_nn/test_functional/test_pooling.py

@@ -276,6 +276,41 @@ def test_paddle_avg_pool2d(
     )
 
 
+# max_pool3d
+@handle_frontend_test(
+    fn_tree="paddle.nn.functional.max_pool3d",
+    x_k_s_p=helpers.arrays_for_pooling(min_dims=5, max_dims=5, min_side=1, max_side=5),
+    stride=st.tuples(st.integers(1, 2), st.integers(1, 2)),
+    test_with_out=st.just(False),
+)
+def test_paddle_max_pool3d(
+    *,
+    x_k_s_p,
+    stride,
+    data_format,
+    frontend,
+    test_flags,
+    fn_tree,
+    backend_fw,
+    on_device,
+):
+    input_dtype, x, kernel_size, _, padding = x_k_s_p
+    data_format = data_format
+    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,
+        x=x[0],
+        kernel_size=kernel_size,
+        stride=stride,
+        padding=padding,
+        data_format=data_format,
+    )
+
+
 # max_unpool1d
 @handle_frontend_test(
     fn_tree="paddle.nn.functional.max_unpool1d",