wehub-resource-sync
147 lines
3.7 KiB
Python
147 lines
3.7 KiB
Python
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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import numpy as np
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from op import Operator
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from op_test import (
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OpTest,
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convert_float_to_uint16,
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get_device_place,
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get_places,
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is_custom_device,
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)
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import paddle
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from paddle.base import core
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class TestShapeOp(OpTest):
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def setUp(self):
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self.op_type = "shape"
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self.python_api = paddle.shape
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self.config()
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input = np.zeros(self.shape, dtype=self.dtype)
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self.inputs = {'Input': input}
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self.outputs = {'Out': np.array(self.shape)}
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def config(self):
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self.shape = [2, 3]
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self.dtype = np.float32
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def test_check_output(self):
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self.check_output(check_cinn=True, check_pir=True)
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class case1(TestShapeOp):
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def config(self):
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self.shape = [2]
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self.dtype = np.float32
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class case2(TestShapeOp):
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def config(self):
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self.shape = [1, 2, 3]
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self.dtype = np.float32
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class TestShapeOpFp16(TestShapeOp):
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def config(self):
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self.shape = [2, 3]
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self.dtype = np.float16
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class case1Fp16(TestShapeOp):
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def config(self):
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self.shape = [2]
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self.dtype = np.float16
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class case2Fp16(TestShapeOp):
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def config(self):
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self.shape = [1, 2, 3]
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self.dtype = np.float16
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class TestShapeWithSelectedRows(unittest.TestCase):
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def get_places(self):
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return get_places()
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def check_with_place(self, place):
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scope = core.Scope()
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x_rows = [0, 1, 5, 4, 19]
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height = 20
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row_numel = 2
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np_array = np.ones((len(x_rows), row_numel)).astype("float32")
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# initialize input variable X
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x = scope.var('X').get_selected_rows()
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x.set_rows(x_rows)
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x.set_height(height)
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x_tensor = x.get_tensor()
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x_tensor.set(np_array, place)
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# initialize input variable Out
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out_shape = scope.var("Out").get_tensor()
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op = Operator("shape", Input="X", Out="Out")
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op.run(scope, place)
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out_shape = np.array(out_shape).tolist()
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self.assertListEqual([5, 2], out_shape)
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def test_check_output(self):
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for place in self.get_places():
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self.check_with_place(place)
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@unittest.skipIf(
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not (core.is_compiled_with_cuda() or is_custom_device())
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or not core.is_bfloat16_supported(get_device_place()),
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"core is not compiled with CUDA or place do not support bfloat16",
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)
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class TestShapeOpBf16(OpTest):
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def setUp(self):
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self.op_type = "shape"
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self.dtype = 'bfloat16'
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self.python_api = paddle.shape
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self.config()
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input = np.zeros(self.shape)
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input = convert_float_to_uint16(input.astype('float32'))
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self.inputs = {'Input': input}
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self.outputs = {'Out': np.array(self.shape)}
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def config(self):
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self.shape = [2, 3]
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def test_check_output(self):
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place = get_device_place()
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self.check_output_with_place(place, check_cinn=True, check_pir=True)
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class case1Bf16(TestShapeOpBf16):
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def config(self):
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self.shape = [2]
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class case2Bf16(TestShapeOpBf16):
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def config(self):
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self.shape = [1, 2, 3]
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if __name__ == '__main__':
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unittest.main()
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