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Fix conv2d unittest error and support custom device #74839

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Merged
merged 1 commit into from
Aug 25, 2025
Merged

Fix conv2d unittest error and support custom device #74839

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19 changes: 13 additions & 6 deletions test/legacy_test/op_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -60,6 +60,7 @@
from paddle.autograd.ir_backward import grad as ir_grad
from paddle.base import Scope, core, unique_name
from paddle.base.backward import append_backward
from paddle.base.core import DataType, VarDesc
from paddle.base.executor import Executor, scope_guard
from paddle.base.framework import (
OpProtoHolder,
Expand Down Expand Up @@ -164,19 +165,25 @@ def product(dim):
tensor_to_check = scope.find_var(input_to_check).get_tensor()
tensor_size = product(tensor_to_check.shape())
tensor_to_check_dtype = tensor_to_check._dtype()
if tensor_to_check_dtype == paddle.float32:
if tensor_to_check_dtype in [VarDesc.VarType.FP32, DataType.FLOAT32]:
tensor_to_check_dtype = np.float32
elif tensor_to_check_dtype == paddle.float64:
elif tensor_to_check_dtype in [VarDesc.VarType.FP64, DataType.FLOAT64]:
tensor_to_check_dtype = np.float64
elif tensor_to_check_dtype == paddle.float16:
elif tensor_to_check_dtype in [VarDesc.VarType.FP16, DataType.FLOAT16]:
tensor_to_check_dtype = np.float16
# set delta as np.float16, will automatic convert to float32, float64
delta = np.array(delta).astype(np.float16)
elif tensor_to_check_dtype == paddle.bfloat16:
elif tensor_to_check_dtype in [VarDesc.VarType.BF16, DataType.BFLOAT16]:
tensor_to_check_dtype = np.float32
elif tensor_to_check_dtype == paddle.complex64:
elif tensor_to_check_dtype in [
VarDesc.VarType.COMPLEX64,
DataType.COMPLEX64,
]:
tensor_to_check_dtype = np.complex64
elif tensor_to_check_dtype == paddle.complex128:
elif tensor_to_check_dtype in [
VarDesc.VarType.COMPLEX128,
DataType.COMPLEX128,
]:
tensor_to_check_dtype = np.complex128
else:
raise ValueError(
Expand Down
53 changes: 30 additions & 23 deletions test/legacy_test/test_conv2d_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,13 @@
import unittest

import numpy as np
from op_test import OpTest, convert_float_to_uint16, get_numeric_gradient
from op_test import (
OpTest,
convert_float_to_uint16,
get_device_place,
get_numeric_gradient,
is_custom_device,
)
from testsuite import create_op

import paddle
Expand Down Expand Up @@ -162,7 +168,8 @@ def init_kernel_type(self):

def create_test_cudnn_fp16_class(parent, grad_check=True):
@unittest.skipIf(
not core.is_compiled_with_cuda(), "core is not compiled with CUDA"
not (core.is_compiled_with_cuda() or is_custom_device()),
"core is not compiled with CUDA",
)
class TestConv2DCUDNNFp16(parent):
def init_kernel_type(self):
Expand All @@ -171,19 +178,19 @@ def init_kernel_type(self):

def test_check_output(self):
if core.is_compiled_with_cuda():
place = core.CUDAPlace(0)
place = get_device_place()
if core.is_float16_supported(place):
self.check_output_with_place(place, atol=2e-2)

def test_check_grad_no_filter(self):
place = core.CUDAPlace(0)
place = get_device_place()
if core.is_float16_supported(place) and grad_check:
self.check_grad_with_place(
place, ['Input'], 'Output', no_grad_set={'Filter'}
)

def test_check_grad_no_input(self):
place = core.CUDAPlace(0)
place = get_device_place()
if core.is_float16_supported(place) and grad_check:
self.check_grad_with_place(
place, ['Filter'], 'Output', no_grad_set={'Input'}
Expand All @@ -196,8 +203,8 @@ def test_check_grad_no_input(self):

def create_test_cudnn_bf16_class(parent):
@unittest.skipIf(
not core.is_compiled_with_cuda()
or not core.is_bfloat16_supported(core.CUDAPlace(0)),
not (core.is_compiled_with_cuda() or is_custom_device())
or not core.is_bfloat16_supported(get_device_place()),
"core is not compiled with CUDA and do not support bfloat16",
)
class TestConv2DCUDNNBF16(parent):
Expand All @@ -217,11 +224,11 @@ def init_kernel_type(self):
self.dtype = np.uint16

def test_check_output(self):
place = core.CUDAPlace(0)
place = get_device_place()
self.check_output_with_place(place, atol=1e-2)

def test_check_grad_no_filter(self):
place = core.CUDAPlace(0)
place = get_device_place()
numeric_grads = self.get_numeric_grad(place, 'Input')
self.check_grad_with_place(
place,
Expand All @@ -232,7 +239,7 @@ def test_check_grad_no_filter(self):
)

def test_check_grad_no_input(self):
place = core.CUDAPlace(0)
place = get_device_place()
numeric_grads = self.get_numeric_grad(place, 'Filter')
self.check_grad_with_place(
place,
Expand Down Expand Up @@ -294,20 +301,20 @@ def init_kernel_type(self):
self.dtype = np.float16

def test_check_output(self):
if core.is_compiled_with_cuda():
place = core.CUDAPlace(0)
if core.is_compiled_with_cuda() or is_custom_device():
place = get_device_place()
if core.is_float16_supported(place):
self.check_output_with_place(place, atol=2e-2)

def test_check_grad_no_filter(self):
place = core.CUDAPlace(0)
place = get_device_place()
if core.is_float16_supported(place) and grad_check:
self.check_grad_with_place(
place, ['Input'], 'Output', no_grad_set={'Filter'}
)

def test_check_grad_no_input(self):
place = core.CUDAPlace(0)
place = get_device_place()
if core.is_float16_supported(place) and grad_check:
self.check_grad_with_place(
place, ['Filter'], 'Output', no_grad_set={'Input'}
Expand Down Expand Up @@ -491,12 +498,12 @@ def setUp(self):
self.outputs = {'Output': output}

def has_cuda(self):
return core.is_compiled_with_cuda() and (
return (core.is_compiled_with_cuda() or is_custom_device()) and (
self.use_cudnn or self.use_cuda
)

def test_check_output(self):
place = core.CUDAPlace(0) if self.has_cuda() else core.CPUPlace()
place = get_device_place() if self.has_cuda() else core.CPUPlace()
# TODO(wangzhongpu): support onednn op in dygraph mode
self.check_output_with_place(
place,
Expand All @@ -510,7 +517,7 @@ def test_check_grad(self):
hasattr(self, "no_need_check_grad") and self.no_need_check_grad
):
return
place = core.CUDAPlace(0) if self.has_cuda() else core.CPUPlace()
place = get_device_place() if self.has_cuda() else core.CPUPlace()
# TODO(wangzhongpu): support onednn op in dygraph mode
self.check_grad_with_place(
place,
Expand All @@ -526,7 +533,7 @@ def test_check_grad_no_filter(self):
hasattr(self, "no_need_check_grad") and self.no_need_check_grad
):
return
place = core.CUDAPlace(0) if self.has_cuda() else core.CPUPlace()
place = get_device_place() if self.has_cuda() else core.CPUPlace()
# TODO(wangzhongpu): support onednn op in dygraph mode
self.check_grad_with_place(
place,
Expand All @@ -543,7 +550,7 @@ def test_check_grad_no_input(self):
hasattr(self, "no_need_check_grad") and self.no_need_check_grad
):
return
place = core.CUDAPlace(0) if self.has_cuda() else core.CPUPlace()
place = get_device_place() if self.has_cuda() else core.CPUPlace()
# TODO(wangzhongpu): support onednn op in dygraph mode
self.check_grad_with_place(
place,
Expand Down Expand Up @@ -830,7 +837,7 @@ def has_cuda(self):

def test_check_output(self):
# TODO(wangzhongpu): support onednn op in dygraph mode
place = core.CUDAPlace(0) if self.has_cuda() else core.CPUPlace()
place = get_device_place() if self.has_cuda() else core.CPUPlace()
self.check_output_with_place(
place,
atol=1e-5,
Expand All @@ -842,7 +849,7 @@ def test_check_grad(self):
# TODO(wangzhongpu): support onednn op in dygraph mode
if self.dtype == np.float16:
return
place = core.CUDAPlace(0) if self.has_cuda() else core.CPUPlace()
place = get_device_place() if self.has_cuda() else core.CPUPlace()
self.check_grad_with_place(
place,
{'Input', 'Filter'},
Expand All @@ -856,7 +863,7 @@ def test_check_grad_no_filter(self):
# TODO(wangzhongpu): support onednn op in dygraph mode
if self.dtype == np.float16:
return
place = core.CUDAPlace(0) if self.has_cuda() else core.CPUPlace()
place = get_device_place() if self.has_cuda() else core.CPUPlace()
self.check_grad_with_place(
place,
['Input'],
Expand All @@ -871,7 +878,7 @@ def test_check_grad_no_input(self):
# TODO(wangzhongpu): support onednn op in dygraph mode
if self.dtype == np.float16:
return
place = core.CUDAPlace(0) if self.has_cuda() else core.CPUPlace()
place = get_device_place() if self.has_cuda() else core.CPUPlace()
self.check_grad_with_place(
place,
['Filter'],
Expand Down