wehub-resource-sync
175 lines
6.2 KiB
Python
175 lines
6.2 KiB
Python
# Copyright (c) 2019 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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from op_test import get_device, is_custom_device
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import paddle
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from paddle import base
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class TensorToTest(unittest.TestCase):
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def test_Tensor_to_dtype(self):
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tensorx = paddle.to_tensor([1, 2, 3])
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valid_dtypes = [
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"bfloat16",
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"float16",
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"float32",
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"float64",
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"int8",
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"int16",
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"int32",
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"int64",
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"uint8",
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"bool",
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] + (
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[]
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if base.core.is_compiled_with_xpu()
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else ["complex64", "complex128"]
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)
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for dtype in valid_dtypes:
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tensorx = tensorx.to(dtype)
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typex_str = str(tensorx.dtype)
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self.assertTrue(typex_str, "paddle." + dtype)
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def test_Tensor_to_device(self):
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tensorx = paddle.to_tensor([1, 2, 3])
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places = ["cpu"]
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if base.core.is_compiled_with_cuda() or is_custom_device():
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places.append(get_device(True))
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places.append(get_device())
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if base.core.is_compiled_with_xpu():
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places.append("xpu:0")
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places.append("xpu")
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for place in places:
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tensorx = tensorx.to(place)
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placex_str = str(tensorx.place)
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if place == get_device() or place == "xpu":
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self.assertTrue(placex_str, "Place(" + place + ":0)")
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else:
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self.assertTrue(placex_str, "Place(" + place + ")")
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def test_Tensor_to_device2(self):
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x = paddle.to_tensor([1, 2, 3])
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y = paddle.to_tensor([1, 2, 3], place="cpu")
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y.to(x.place)
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self.assertTrue(x.place, y.place)
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def test_Tensor_to_device_dtype(self):
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tensorx = paddle.to_tensor([1, 2, 3])
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places = ["cpu"]
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if base.core.is_compiled_with_cuda() or is_custom_device():
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places.append(get_device(True))
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places.append(get_device())
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if base.core.is_compiled_with_xpu():
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places.append("xpu:0")
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places.append("xpu")
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valid_dtypes = [
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"bfloat16",
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"float16",
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"float32",
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"float64",
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"int8",
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"int16",
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"int32",
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"int64",
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"uint8",
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"bool",
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] + (
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[]
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if base.core.is_compiled_with_xpu()
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else ["complex64", "complex128"]
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)
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for dtype in valid_dtypes:
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for place in places:
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tensorx = tensorx.to(place, dtype)
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placex_str = str(tensorx.place)
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if place == get_device() or place == "xpu":
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self.assertTrue(placex_str, "Place(" + place + ":0)")
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else:
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self.assertTrue(placex_str, "Place(" + place + ")")
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typex_str = str(tensorx.dtype)
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self.assertTrue(typex_str, "paddle." + dtype)
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def test_Tensor_to_blocking(self):
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tensorx = paddle.to_tensor([1, 2, 3])
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tensorx = tensorx.to("cpu", "int32", False)
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placex_str = str(tensorx.place)
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self.assertTrue(placex_str, "Place(cpu)")
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typex_str = str(tensorx.dtype)
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self.assertTrue(typex_str, "paddle.int32")
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tensor2 = paddle.to_tensor([4, 5, 6])
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tensor2 = tensor2.to(tensorx, False)
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place2_str = str(tensor2.place)
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self.assertTrue(place2_str, "Place(cpu)")
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type2_str = str(tensor2.dtype)
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self.assertTrue(type2_str, "paddle.int32")
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tensor2 = tensor2.to("float16", False)
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type2_str = str(tensor2.dtype)
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self.assertTrue(type2_str, "paddle.float16")
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def test_Tensor_to_other(self):
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tensor1 = paddle.to_tensor([1, 2, 3], dtype="int8", place="cpu")
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tensor2 = paddle.to_tensor([1, 2, 3])
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tensor2 = tensor2.to(tensor1)
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self.assertTrue(tensor2.dtype, tensor1.dtype)
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self.assertTrue(type(tensor2.place), type(tensor1.place))
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def test_kwargs(self):
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tensorx = paddle.to_tensor([1, 2, 3])
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tensorx = tensorx.to(device="cpu", dtype="int8", blocking=True)
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placex_str = str(tensorx.place)
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self.assertTrue(placex_str, "Place(cpu)")
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typex_str = str(tensorx.dtype)
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self.assertTrue(typex_str, "paddle.int8")
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tensor2 = paddle.to_tensor([4, 5, 6])
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tensor2 = tensor2.to(other=tensorx)
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place2_str = str(tensor2.place)
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self.assertTrue(place2_str, "Place(cpu)")
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type2_str = str(tensor2.dtype)
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self.assertTrue(type2_str, "paddle.int8")
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tensor3 = paddle.to_tensor([7, 8, 9])
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tensor4 = tensor3.to(dtype="int8", non_blocking=True)
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self.assertTrue(tensor4.dtype, "paddle.int8")
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tensor5 = tensor3.to(dtype="int8", copy=True)
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self.assertTrue(tensor5.dtype, "paddle.int8")
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tensor6 = tensor3.to(dtype="int8", non_blocking=True, copy=True)
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self.assertTrue(tensor6.dtype, "paddle.int8")
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tensor7 = tensor3.to(dtype=tensor3.dtype, copy=True)
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self.assertTrue(tensor7.dtype, tensor3.dtype)
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def test_error(self):
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tensorx = paddle.to_tensor([1, 2, 3])
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# device value error
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try:
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tensorx = tensorx.to("error_device")
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except Exception as error:
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self.assertIsInstance(error, ValueError)
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# to many augments
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try:
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tensorx = tensorx.to("cpu", "int32", False, "test_aug")
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except Exception as error:
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self.assertIsInstance(error, TypeError)
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# invalid key
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try:
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tensorx = tensorx.to("cpu", "int32", test_key=False)
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except Exception as error:
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self.assertIsInstance(error, TypeError)
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if __name__ == '__main__':
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unittest.main()
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