From bb89c0c855113f55b107afaa0c5f1a2bfe434ba8 Mon Sep 17 00:00:00 2001 From: Charles-hit <56987902+Charles-hit@users.noreply.github.com> Date: Thu, 8 Jun 2023 11:33:51 +0800 Subject: [PATCH] [AMP Prim OP]support some prim ops for bf16 dtype part5 (#54422) * support some prim ops for bf16 dtype * remove useless code --- test/legacy_test/CMakeLists.txt | 4 +- test/legacy_test/test_elementwise_min_op.py | 25 +------ test/legacy_test/test_pad_op.py | 7 +- test/legacy_test/test_roll_op.py | 3 - test/legacy_test/test_scatter_op.py | 76 ++++++++++++++++---- test/legacy_test/test_split_op.py | 3 +- test/legacy_test/test_squeeze2_op.py | 77 +++++++++++++++++++-- test/legacy_test/test_stack_op.py | 4 +- test/legacy_test/test_tile_op.py | 18 +++-- test/legacy_test/test_unsqueeze2_op.py | 9 +-- 10 files changed, 165 insertions(+), 61 deletions(-) diff --git a/test/legacy_test/CMakeLists.txt b/test/legacy_test/CMakeLists.txt index 437f83a900b..67142d60a72 100644 --- a/test/legacy_test/CMakeLists.txt +++ b/test/legacy_test/CMakeLists.txt @@ -1197,7 +1197,9 @@ set(TEST_CINN_OPS test_scatter_nd_op test_strided_slice_op test_instance_norm_op - test_cumsum_op) + test_cumsum_op + test_pad_op + test_split_op) foreach(TEST_CINN_OPS ${TEST_CINN_OPS}) if(WITH_CINN) diff --git a/test/legacy_test/test_elementwise_min_op.py b/test/legacy_test/test_elementwise_min_op.py index fb03a6831ad..9ba527ef803 100644 --- a/test/legacy_test/test_elementwise_min_op.py +++ b/test/legacy_test/test_elementwise_min_op.py @@ -127,18 +127,12 @@ class TestElementwiseMinOp_ZeroDim1(TestElementwiseOp): self.inputs = {'X': x, 'Y': y} self.outputs = {'Out': np.minimum(self.inputs['X'], self.inputs['Y'])} - def if_enable_cinn(self): - self.enable_cinn = False - class TestElementwiseMinFP16Op_ZeroDim1(TestElementwiseFP16Op): def init_data(self): self.x = np.random.uniform(0.1, 1, []).astype(np.float16) self.y = np.random.uniform(0.1, 1, []).astype(np.float16) - def if_enable_cinn(self): - self.enable_cinn = False - class TestElementwiseMinOp_ZeroDim2(TestElementwiseOp): def setUp(self): @@ -146,24 +140,17 @@ class TestElementwiseMinOp_ZeroDim2(TestElementwiseOp): self.python_api = paddle.minimum self.public_python_api = paddle.minimum self.prim_op_type = "prim" - self.if_enable_cinn() x = np.random.uniform(0.1, 1, [13, 17]).astype("float64") y = np.random.uniform(0.1, 1, []).astype("float64") self.inputs = {'X': x, 'Y': y} self.outputs = {'Out': np.minimum(self.inputs['X'], self.inputs['Y'])} - def if_enable_cinn(self): - self.enable_cinn = False - class TestElementwiseMinFP16Op_ZeroDim2(TestElementwiseFP16Op): def init_data(self): self.x = np.random.uniform(0.1, 1, [13, 17]).astype("float16") self.y = np.random.uniform(0.1, 1, []).astype("float16") - def if_enable_cinn(self): - self.enable_cinn = False - class TestElementwiseMinOp_ZeroDim3(TestElementwiseOp): def setUp(self): @@ -177,18 +164,12 @@ class TestElementwiseMinOp_ZeroDim3(TestElementwiseOp): self.inputs = {'X': x, 'Y': y} self.outputs = {'Out': np.minimum(self.inputs['X'], self.inputs['Y'])} - def if_enable_cinn(self): - self.enable_cinn = False - class TestElementwiseMinFP16Op_ZeroDim3(TestElementwiseFP16Op): def init_data(self): self.x = np.random.uniform(0.1, 1, []).astype("float16") self.y = np.random.uniform(0.1, 1, [13, 17]).astype("float16") - def if_enable_cinn(self): - self.enable_cinn = False - @skip_check_grad_ci( reason="[skip shape check] Use y_shape(1) to test broadcast." @@ -388,7 +369,7 @@ class TestElementwiseBF16Op(OpTest): def test_check_grad_ingore_x(self): places = self._get_places() for place in places: - if type(place) is paddle.fluid.libpaddle.CPUPlace: + if isinstance(place, paddle.fluid.libpaddle.CPUPlace): check_prim = False else: check_prim = True @@ -413,7 +394,7 @@ class TestElementwiseBF16Op(OpTest): def test_check_grad_ingore_y(self): places = self._get_places() for place in places: - if type(place) is paddle.fluid.libpaddle.CPUPlace: + if isinstance(place, paddle.fluid.libpaddle.CPUPlace): check_prim = False else: check_prim = True @@ -436,7 +417,7 @@ class TestElementwiseBF16Op(OpTest): ) def if_enable_cinn(self): - self.enable_cinn = False + pass class TestElementwiseMinBF16Op_ZeroDim1(TestElementwiseBF16Op): diff --git a/test/legacy_test/test_pad_op.py b/test/legacy_test/test_pad_op.py index a25956cfb06..3cec8719e13 100644 --- a/test/legacy_test/test_pad_op.py +++ b/test/legacy_test/test_pad_op.py @@ -100,7 +100,7 @@ def create_test_fp16(parent): return np.float16 def test_check_grad_normal(self): - self.check_grad(['X'], 'Out') + self.check_grad(['X'], 'Out', check_prim=True) cls_name = "{}_{}".format(parent.__name__, "Fp16") TestPadFp16.__name__ = cls_name @@ -238,9 +238,12 @@ class TestPadBP16Op(OpTest): ) self.inputs = {'X': convert_float_to_uint16(x)} self.outputs = {'Out': convert_float_to_uint16(out)} - self.enable_cinn = False self.prim_op_type = "prim" self.public_python_api = pad_wrapper + self.if_enable_cinn() + + def if_enable_cinn(self): + pass def initTestCase(self): self.shape = (16, 16) diff --git a/test/legacy_test/test_roll_op.py b/test/legacy_test/test_roll_op.py index 1dab474ac26..f491112b6a4 100644 --- a/test/legacy_test/test_roll_op.py +++ b/test/legacy_test/test_roll_op.py @@ -53,9 +53,6 @@ class TestRollOp(OpTest): def test_check_grad_normal(self): self.check_grad(['X'], 'Out', check_prim=True) - def test_check_grad(self): - self.check_grad(['X'], 'Out', check_prim=True) - class TestRollOpCase2(TestRollOp): def init_dtype_type(self): diff --git a/test/legacy_test/test_scatter_op.py b/test/legacy_test/test_scatter_op.py index 2a222c9d96a..df264887c62 100644 --- a/test/legacy_test/test_scatter_op.py +++ b/test/legacy_test/test_scatter_op.py @@ -31,6 +31,7 @@ class TestScatterOp(OpTest): self.public_python_api = paddle.scatter self.prim_op_type = "prim" self._set_dtype() + self.if_enable_cinn() target_dtype = "float16" if self.dtype == np.float16 else "float32" ref_np = np.ones((3, 50)).astype(target_dtype) index_np = np.array([1, 2]).astype("int32") @@ -44,11 +45,14 @@ class TestScatterOp(OpTest): self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np} self.outputs = {'Out': output_np} + def if_enable_cinn(self): + pass + def _set_dtype(self): self.dtype = np.float32 def test_check_output(self): - self.check_output(check_prim=True) + self.check_output() def test_check_grad(self): self.check_grad(["X", "Updates"], "Out", check_prim=True) @@ -67,12 +71,14 @@ class TestScatterFP16Op(TestScatterOp): class TestScatterBF16Op(TestScatterOp): def _set_dtype(self): self.dtype = np.uint16 + + def if_enable_cinn(self): self.enable_cinn = False def test_check_output(self): if core.is_compiled_with_cuda(): place = core.CUDAPlace(0) - self.check_output_with_place(place, check_prim=True) + self.check_output_with_place(place) def test_check_grad(self): if core.is_compiled_with_cuda(): @@ -91,6 +97,7 @@ class TestScatterOp0(OpTest): self.python_api = paddle.scatter self.public_python_api = paddle.scatter self.prim_op_type = "prim" + self.if_enable_cinn() self._set_dtype() target_dtype = "float16" if self.dtype == np.float16 else "float32" ref_np = np.ones((3, 3)).astype(target_dtype) @@ -106,11 +113,14 @@ class TestScatterOp0(OpTest): self.attrs = {'overwrite': True} self.outputs = {'Out': output_np} + def if_enable_cinn(self): + pass + def _set_dtype(self): self.dtype = np.float32 def test_check_output(self): - self.check_output(check_prim=True) + self.check_output() def test_check_grad(self): self.check_grad(["X", "Updates"], "Out", check_prim=True) @@ -129,12 +139,14 @@ class TestScatterFP16Op0(TestScatterOp0): class TestScatterBF16Op0(TestScatterOp0): def _set_dtype(self): self.dtype = np.uint16 + + def if_enable_cinn(self): self.enable_cinn = False def test_check_output(self): if core.is_compiled_with_cuda(): place = core.CUDAPlace(0) - self.check_output_with_place(place, check_prim=True) + self.check_output_with_place(place) def test_check_grad(self): if core.is_compiled_with_cuda(): @@ -154,6 +166,7 @@ class TestScatterOp1(OpTest): self.public_python_api = paddle.scatter self.prim_op_type = "prim" self._set_dtype() + self.if_enable_cinn() target_dtype = "float16" if self.dtype == np.float16 else "float32" ref_np = np.ones((3, 3)).astype(target_dtype) zeros_np = np.zeros([2, 3]).astype(target_dtype) @@ -171,11 +184,14 @@ class TestScatterOp1(OpTest): self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np} self.outputs = {'Out': output_np} + def if_enable_cinn(self): + pass + def _set_dtype(self): self.dtype = np.float32 def test_check_output(self): - self.check_output(check_prim=True) + self.check_output() def test_check_grad(self): self.check_grad(["X", "Updates"], "Out", check_prim=True) @@ -194,12 +210,14 @@ class TestScatterFP16Op1(TestScatterOp1): class TestScatterBF16Op1(TestScatterOp1): def _set_dtype(self): self.dtype = np.uint16 + + def if_enable_cinn(self): self.enable_cinn = False def test_check_output(self): if core.is_compiled_with_cuda(): place = core.CUDAPlace(0) - self.check_output_with_place(place, check_prim=True) + self.check_output_with_place(place) def test_check_grad(self): if core.is_compiled_with_cuda(): @@ -222,6 +240,7 @@ class TestScatterOp2(OpTest): self.public_python_api = paddle.scatter self.prim_op_type = "prim" self._set_dtype() + self.if_enable_cinn() target_dtype = "float16" if self.dtype == np.float16 else "float32" ref_np = np.ones((3, 3)).astype(target_dtype) index_np = np.array([1, 2]).astype("int32") @@ -235,13 +254,16 @@ class TestScatterOp2(OpTest): self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np} self.outputs = {'Out': output_np} + def if_enable_cinn(self): + pass + def _set_dtype(self): self.dtype = np.float32 def test_check_output(self): if core.is_compiled_with_cuda(): place = core.CUDAPlace(0) - self.check_output_with_place(place, atol=1e-3, check_prim=True) + self.check_output_with_place(place, atol=1e-3) def test_check_grad(self): if core.is_compiled_with_cuda(): @@ -270,6 +292,8 @@ class TestScatterFP16Op2(TestScatterOp2): class TestScatterBF16Op2(TestScatterOp2): def _set_dtype(self): self.dtype = np.uint16 + + def if_enable_cinn(self): self.enable_cinn = False @@ -283,6 +307,7 @@ class TestScatterOp3(OpTest): self.public_python_api = paddle.scatter self.prim_op_type = "prim" self._set_dtype() + self.if_enable_cinn() target_dtype = "float16" if self.dtype == np.float16 else "float32" ref_np = np.ones((3, 3)).astype(target_dtype) zeros_np = np.zeros([2, 3]).astype(target_dtype) @@ -300,13 +325,16 @@ class TestScatterOp3(OpTest): self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np} self.outputs = {'Out': output_np} + def if_enable_cinn(self): + pass + def _set_dtype(self): self.dtype = np.float32 def test_check_output(self): if core.is_compiled_with_cuda(): place = core.CUDAPlace(0) - self.check_output_with_place(place, atol=1e-3, check_prim=True) + self.check_output_with_place(place, atol=1e-3) def test_check_grad(self): if core.is_compiled_with_cuda(): @@ -335,6 +363,8 @@ class TestScatterFP16Op3(TestScatterOp3): class TestScatterBF16Op3(TestScatterOp3): def _set_dtype(self): self.dtype = np.uint16 + + def if_enable_cinn(self): self.enable_cinn = False @@ -345,6 +375,7 @@ class TestScatterOp4(OpTest): self.public_python_api = paddle.scatter self.prim_op_type = "prim" self._set_dtype() + self.if_enable_cinn() target_dtype = "float16" if self.dtype == np.float16 else "float32" ref_np = np.ones((3, 3)).astype(target_dtype) index_np = np.array([1, 2]).astype("int64") @@ -358,11 +389,14 @@ class TestScatterOp4(OpTest): self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np} self.outputs = {'Out': output_np} + def if_enable_cinn(self): + pass + def _set_dtype(self): self.dtype = np.float32 def test_check_output(self): - self.check_output(check_prim=True) + self.check_output() def test_check_grad(self): self.check_grad(['X', 'Updates'], 'Out', check_prim=True) @@ -381,12 +415,14 @@ class TestScatterFP16Op4(TestScatterOp4): class TestScatterBF16Op4(TestScatterOp4): def _set_dtype(self): self.dtype = np.uint16 + + def if_enable_cinn(self): self.enable_cinn = False def test_check_output(self): if core.is_compiled_with_cuda(): place = core.CUDAPlace(0) - self.check_output_with_place(place, check_prim=True) + self.check_output_with_place(place) def test_check_grad(self): if core.is_compiled_with_cuda(): @@ -409,6 +445,7 @@ class TestScatterOp5(OpTest): self.public_python_api = paddle.scatter self.prim_op_type = "prim" self._set_dtype() + self.if_enable_cinn() target_dtype = "float16" if self.dtype == np.float16 else "float32" ref_np = np.ones((3, 3)).astype(target_dtype) index_np = np.array([1, 2]).astype("int64") @@ -422,13 +459,16 @@ class TestScatterOp5(OpTest): self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np} self.outputs = {'Out': output_np} + def if_enable_cinn(self): + pass + def _set_dtype(self): self.dtype = np.float32 def test_check_output(self): if core.is_compiled_with_cuda(): place = core.CUDAPlace(0) - self.check_output_with_place(place, atol=1e-3, check_prim=True) + self.check_output_with_place(place, atol=1e-3) def test_check_grad(self): if core.is_compiled_with_cuda(): @@ -457,6 +497,8 @@ class TestScatterFP16Op5(TestScatterOp5): class TestScatterBF16Op5(TestScatterOp5): def _set_dtype(self): self.dtype = np.uint16 + + def if_enable_cinn(self): self.enable_cinn = False @@ -466,7 +508,7 @@ class TestScatterOp6(OpTest): self.python_api = paddle.scatter self.public_python_api = paddle.scatter self.prim_op_type = "prim" - self.enable_cinn = False + self.if_enable_cinn() self._set_dtype() target_dtype = "float16" if self.dtype == np.float16 else "float32" ref_np = np.ones((3, 50)).astype(target_dtype) @@ -481,11 +523,14 @@ class TestScatterOp6(OpTest): self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np} self.outputs = {'Out': output_np} + def if_enable_cinn(self): + pass + def _set_dtype(self): self.dtype = np.float32 def test_check_output(self): - self.check_output(check_prim=True) + self.check_output() def test_check_grad(self): self.check_grad(["X", "Updates"], "Out", check_prim=True) @@ -502,13 +547,16 @@ class TestScatterFP16Op6(TestScatterOp6): "core is not complied with CUDA and not support the bfloat16", ) class TestScatterBF16Op6(TestScatterOp6): + def if_enable_cinn(self): + self.enable_cinn = False + def _set_dtype(self): self.dtype = np.uint16 def test_check_output(self): if core.is_compiled_with_cuda(): place = core.CUDAPlace(0) - self.check_output_with_place(place, check_prim=True) + self.check_output_with_place(place) def test_check_grad(self): if core.is_compiled_with_cuda(): diff --git a/test/legacy_test/test_split_op.py b/test/legacy_test/test_split_op.py index 29446bafbbf..87829f503cc 100644 --- a/test/legacy_test/test_split_op.py +++ b/test/legacy_test/test_split_op.py @@ -32,7 +32,6 @@ class TestSplitOp(OpTest): self.dtype = self.get_dtype() axis = 1 if self.dtype == np.uint16: - self.enable_cinn = False x = np.random.random((4, 5, 6)).astype(np.float32) out = np.split(x, [2, 3], axis) self.inputs = {'X': convert_float_to_uint16(x)} @@ -285,7 +284,7 @@ def create_test_bf16(parent): def test_check_grad(self): place = core.CUDAPlace(0) - self.check_grad_with_place(place, ['X'], 'out2') + self.check_grad_with_place(place, ['X'], 'out2', check_prim=True) cls_name = "{}_{}".format(parent.__name__, "BF16Op") TestSplitBF16Op.__name__ = cls_name diff --git a/test/legacy_test/test_squeeze2_op.py b/test/legacy_test/test_squeeze2_op.py index 8a5c5e74efc..c2bef8aa822 100755 --- a/test/legacy_test/test_squeeze2_op.py +++ b/test/legacy_test/test_squeeze2_op.py @@ -16,10 +16,11 @@ import os import unittest import numpy as np -from eager_op_test import OpTest +from eager_op_test import OpTest, convert_float_to_uint16 from test_attribute_var import UnittestBase import paddle +from paddle.fluid import core from paddle.fluid.framework import Program, program_guard paddle.enable_static() @@ -36,19 +37,32 @@ class TestSqueezeOp(OpTest): "Out" ] # python out sig is customized output signature. self.init_test_case() - self.inputs = {"X": np.random.random(self.ori_shape).astype("float64")} + self.init_dtype() + self.if_enable_cinn() + x = np.random.random(self.ori_shape).astype("float64") + xshape = np.random.random(self.ori_shape).astype("float64") + if hasattr(self, "dtype") and self.dtype == np.uint16: + x = convert_float_to_uint16(x.astype(np.float32)) + xshape = convert_float_to_uint16(xshape.astype(np.float32)) + self.inputs = {"X": x} self.init_attrs() self.outputs = { "Out": self.inputs["X"].reshape(self.new_shape), - "XShape": np.random.random(self.ori_shape).astype("float64"), + "XShape": xshape, } + def if_enable_cinn(self): + pass + def test_check_output(self): self.check_output(no_check_set=['XShape'], check_prim=True) def test_check_grad(self): self.check_grad(["X"], "Out", check_prim=True) + def init_dtype(self): + self.dtype = np.float64 + def init_test_case(self): self.ori_shape = (1, 3, 1, 40) self.axes = (0, 2) @@ -58,6 +72,16 @@ class TestSqueezeOp(OpTest): self.attrs = {"axes": self.axes} +@unittest.skipIf( + not core.is_compiled_with_cuda() + or not core.is_bfloat16_supported(core.CUDAPlace(0)), + "core is not compiled with CUDA and do not support bfloat16", +) +class TestSqueezeOpBF16OP(TestSqueezeOp): + def init_dtype(self): + self.dtype = np.uint16 + + # Correct: There is mins axis. class TestSqueezeOp1(TestSqueezeOp): def init_test_case(self): @@ -66,6 +90,16 @@ class TestSqueezeOp1(TestSqueezeOp): self.new_shape = (20, 5) +@unittest.skipIf( + not core.is_compiled_with_cuda() + or not core.is_bfloat16_supported(core.CUDAPlace(0)), + "core is not compiled with CUDA and do not support bfloat16", +) +class TestSqueezeOp1BF16Op(TestSqueezeOp): + def init_dtype(self): + self.dtype = np.uint16 + + # Correct: No axes input. class TestSqueezeOp2(TestSqueezeOp): def setUp(self): @@ -77,19 +111,42 @@ class TestSqueezeOp2(TestSqueezeOp): "Out" ] # python out sig is customized output signature. self.init_test_case() - self.inputs = {"X": np.random.random(self.ori_shape).astype("float64")} + self.init_dtype() + self.if_enable_cinn() + x = np.random.random(self.ori_shape).astype("float64") + xshape = np.random.random(self.ori_shape).astype("float64") + if hasattr(self, "dtype") and self.dtype == np.uint16: + x = convert_float_to_uint16(x.astype(np.float32)) + xshape = convert_float_to_uint16(xshape.astype(np.float32)) + self.inputs = {"X": x} self.init_attrs() self.outputs = { "Out": self.inputs["X"].reshape(self.new_shape), - "XShape": np.random.random(self.ori_shape).astype("float64"), + "XShape": xshape, } + def if_enable_cinn(self): + pass + + def init_dtype(self): + self.dtype = np.float64 + def init_test_case(self): self.ori_shape = (1, 20, 1, 5) self.axes = () self.new_shape = (20, 5) +@unittest.skipIf( + not core.is_compiled_with_cuda() + or not core.is_bfloat16_supported(core.CUDAPlace(0)), + "core is not compiled with CUDA and do not support bfloat16", +) +class TestSqueezeOp2BF16Op(TestSqueezeOp): + def init_dtype(self): + self.dtype = np.uint16 + + # Correct: Just part of axes be squeezed. class TestSqueezeOp3(TestSqueezeOp): def init_test_case(self): @@ -98,6 +155,16 @@ class TestSqueezeOp3(TestSqueezeOp): self.new_shape = (6, 5, 1, 4) +@unittest.skipIf( + not core.is_compiled_with_cuda() + or not core.is_bfloat16_supported(core.CUDAPlace(0)), + "core is not compiled with CUDA and do not support bfloat16", +) +class TestSqueezeOp3BF16Op(TestSqueezeOp): + def init_dtype(self): + self.dtype = np.uint16 + + class TestSqueeze2AxesTensor(UnittestBase): def init_info(self): self.shapes = [[2, 3, 4]] diff --git a/test/legacy_test/test_stack_op.py b/test/legacy_test/test_stack_op.py index b6a19615a6e..fea31835120 100644 --- a/test/legacy_test/test_stack_op.py +++ b/test/legacy_test/test_stack_op.py @@ -167,7 +167,6 @@ class TestStackBF16Op(OpTest): self.initParameters() self.op_type = 'stack' self.prim_op_type = "comp" - self.enable_cinn = False self.python_api = paddle.stack self.public_python_api = paddle.stack self.x = [] @@ -191,8 +190,7 @@ class TestStackBF16Op(OpTest): self.check_output(check_prim=True) def test_check_grad(self): - # concat_grad unspport bfloat16 dtype, skip check_prim - self.check_grad(self.get_x_names(), 'Y') + self.check_grad(self.get_x_names(), 'Y', check_prim=True) class TestStackAPIWithLoDTensorArray(unittest.TestCase): diff --git a/test/legacy_test/test_tile_op.py b/test/legacy_test/test_tile_op.py index feca03c5a0c..5267bfa1c58 100644 --- a/test/legacy_test/test_tile_op.py +++ b/test/legacy_test/test_tile_op.py @@ -30,15 +30,18 @@ class TestTileOpRank1(OpTest): self.op_type = "tile" self.python_api = paddle.tile self.prim_op_type = "prim" - self.enable_cinn = True self.public_python_api = paddle.tile self.init_data() + self.if_enable_cinn() self.inputs = {'X': np.random.random(self.ori_shape).astype("float64")} self.attrs = {'repeat_times': self.repeat_times} output = np.tile(self.inputs['X'], self.repeat_times) self.outputs = {'Out': output} + def if_enable_cinn(self): + pass + def init_data(self): self.ori_shape = [100] self.repeat_times = [2] @@ -52,24 +55,30 @@ class TestTileOpRank1(OpTest): class TestTileOpRank_ZeroDim1(TestTileOpRank1): def init_data(self): - self.enable_cinn = False self.ori_shape = [] self.repeat_times = [] + def if_enable_cinn(self): + self.enable_cinn = False + class TestTileOpRank_ZeroDim2(TestTileOpRank1): def init_data(self): - self.enable_cinn = False self.ori_shape = [] self.repeat_times = [2] + def if_enable_cinn(self): + self.enable_cinn = False + class TestTileOpRank_ZeroDim3(TestTileOpRank1): def init_data(self): - self.enable_cinn = False self.ori_shape = [] self.repeat_times = [2, 3] + def if_enable_cinn(self): + self.enable_cinn = False + # with dimension expanding class TestTileOpRank2Expanding(TestTileOpRank1): @@ -240,7 +249,6 @@ class TestTileBF16OP(OpTest): self.__class__.op_type = self.op_type self.python_api = paddle.tile self.prim_op_type = "prim" - self.enable_cinn = False self.public_python_api = paddle.tile self.init_data() x = np.random.uniform(10, size=self.ori_shape).astype(np.float32) diff --git a/test/legacy_test/test_unsqueeze2_op.py b/test/legacy_test/test_unsqueeze2_op.py index b7b4c185e97..2ba8d1204b9 100755 --- a/test/legacy_test/test_unsqueeze2_op.py +++ b/test/legacy_test/test_unsqueeze2_op.py @@ -37,12 +37,16 @@ class TestUnsqueezeOp(OpTest): "XShape": np.random.random(self.ori_shape).astype("float64"), } self.prim_op_type = "comp" + self.if_enable_cinn() + + def if_enable_cinn(self): + pass def test_check_output(self): self.check_output(no_check_set=["XShape"], check_prim=True) def test_check_grad(self): - self.check_grad(["X"], "Out") + self.check_grad(["X"], "Out", check_prim=True) def init_test_case(self): self.ori_shape = (3, 40) @@ -90,7 +94,6 @@ class TestUnsqueezeOp_ZeroDim1(TestUnsqueezeOp): self.ori_shape = () self.axes = (-1,) self.new_shape = 1 - self.enable_cinn = False class TestUnsqueezeOp_ZeroDim2(TestUnsqueezeOp): @@ -98,7 +101,6 @@ class TestUnsqueezeOp_ZeroDim2(TestUnsqueezeOp): self.ori_shape = () self.axes = (-1, 1) self.new_shape = (1, 1) - self.enable_cinn = False class TestUnsqueezeOp_ZeroDim3(TestUnsqueezeOp): @@ -106,7 +108,6 @@ class TestUnsqueezeOp_ZeroDim3(TestUnsqueezeOp): self.ori_shape = () self.axes = (0, 1, 2) self.new_shape = (1, 1, 1) - self.enable_cinn = False # axes is a list(with tensor) -- GitLab