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all cases use large shape and skip special cases #22332

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Jan 17, 2020
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all cases use large shape and skip special cases #22332

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09da24f
all cases use large shape and skip special cases
zhupengyang Jan 16, 2020
c2b7ad6
use large shape for elt-add in mkldnn cases
zhupengyang Jan 16, 2020
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34 changes: 19 additions & 15 deletions python/paddle/fluid/tests/unittests/mkldnn/test_elementwise_add_mkldnn_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,7 +16,7 @@
import unittest
import numpy as np
import paddle.fluid.core as core
from paddle.fluid.tests.unittests.op_test import OpTest
from paddle.fluid.tests.unittests.op_test import OpTest, skip_check_grad_ci
from paddle.fluid.tests.unittests.test_elementwise_add_op import *
'''
Some tests differ from the tests defined in test_elementwise_add_op.py
Expand All @@ -35,6 +35,8 @@ def init_kernel_type(self):
self.use_mkldnn = True


@skip_check_grad_ci(
reason="[skip shape check] Use y_shape(1) to test broadcast.")
class TestMKLDNNElementwiseAddOp_scalar(TestElementwiseAddOp_scalar):
def init_input_output(self):
self.x = np.random.rand(2, 3, 4, 5).astype(self.dtype)
Expand All @@ -45,6 +47,8 @@ def init_kernel_type(self):
self.use_mkldnn = True


@skip_check_grad_ci(
reason="[skip shape check] Use y_shape(1,1) to test broadcast.")
class TestMKLDNNElementwiseAddOp_scalar2(TestElementwiseAddOp_scalar2):
def init_input_output(self):
self.x = np.random.rand(2, 3, 4, 5).astype(self.dtype)
Expand All @@ -62,29 +66,29 @@ def init_kernel_type(self):

class TesMKLDNNtElementwiseAddOp_broadcast_0(TestElementwiseAddOp_broadcast_0):
def init_input_output(self):
self.x = np.random.rand(2, 3, 4, 5).astype(self.dtype)
self.y = np.random.rand(2).astype(self.dtype)
self.out = self.x + self.y.reshape(2, 1, 1, 1)
self.x = np.random.rand(100, 2, 3, 4).astype(self.dtype)
self.y = np.random.rand(100).astype(self.dtype)
self.out = self.x + self.y.reshape(100, 1, 1, 1)

def init_kernel_type(self):
self.use_mkldnn = True


class TestMKLDNNElementwiseAddOp_broadcast_1(TestElementwiseAddOp_broadcast_1):
def init_input_output(self):
self.x = np.random.rand(2, 3, 4, 5).astype(self.dtype)
self.y = np.random.rand(3).astype(self.dtype)
self.out = self.x + self.y.reshape(1, 3, 1, 1)
self.x = np.random.rand(2, 100, 3, 4).astype(self.dtype)
self.y = np.random.rand(100).astype(self.dtype)
self.out = self.x + self.y.reshape(1, 100, 1, 1)

def init_kernel_type(self):
self.use_mkldnn = True


class TestMKLDNNElementwiseAddOp_broadcast_2(TestElementwiseAddOp_broadcast_2):
def init_input_output(self):
self.x = np.random.rand(2, 2, 3, 4).astype(self.dtype)
self.y = np.random.rand(4).astype(self.dtype)
self.out = self.x + self.y.reshape(1, 1, 1, 4)
self.x = np.random.rand(2, 2, 3, 100).astype(self.dtype)
self.y = np.random.rand(100).astype(self.dtype)
self.out = self.x + self.y.reshape(1, 1, 1, 100)

def init_kernel_type(self):
self.use_mkldnn = True
Expand All @@ -103,9 +107,9 @@ def init_kernel_type(self):
class TestMKLDNNElementwiseAddOp_rowwise_add_0(
TestElementwiseAddOp_rowwise_add_0):
def init_input_output(self):
self.x = np.random.rand(2, 3, 4, 5).astype(self.dtype)
self.y = np.random.rand(3, 4).astype(self.dtype)
self.out = self.x + self.y.reshape(1, 3, 4, 1)
self.x = np.random.rand(2, 10, 12, 3).astype(self.dtype)
self.y = np.random.rand(10, 12).astype(self.dtype)
self.out = self.x + self.y.reshape(1, 10, 12, 1)

def init_kernel_type(self):
self.use_mkldnn = True
Expand All @@ -120,8 +124,8 @@ def init_kernel_type(self):
class TestMKLDNNElementwiseAddOp_channelwise_add(
TestElementwiseAddOp_channelwise_add):
def init_input_output(self):
self.x = np.random.rand(3, 5, 20, 20).astype(self.dtype)
self.y = np.random.rand(3, 1, 1, 1).astype(self.dtype)
self.x = np.random.rand(100, 2, 3, 3).astype(self.dtype)
self.y = np.random.rand(100, 1, 1, 1).astype(self.dtype)
self.out = self.x + self.y

def init_kernel_type(self):
Expand Down
1 change: 0 additions & 1 deletion python/paddle/fluid/tests/unittests/op_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -232,7 +232,6 @@ def is_empty_grad_op(op_type):
cls.op_type)

if not get_numeric_gradient.is_large_shape \
and cls.op_type not in check_shape_white_list.NOT_CHECK_OP_LIST \
and cls.op_type not in check_shape_white_list.NEED_TO_FIX_OP_LIST:
raise AssertionError(
"Input's shape should be large than or equal to 100 for " +
Expand Down
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