wehub-resource-sync
94 lines
2.8 KiB
Python
94 lines
2.8 KiB
Python
# Copyright (c) 2022 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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import paddle
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DTYPE_MAP = {
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paddle.bool: np.bool_,
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paddle.int32: np.int32,
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paddle.int64: np.int64,
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paddle.float16: np.float16,
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paddle.float32: np.float32,
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paddle.float64: np.float64,
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paddle.complex64: np.complex64,
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}
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class NumpyScaler2Tensor(unittest.TestCase):
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def setUp(self):
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self.dtype = np.float32
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self.x_np = np.array([1], dtype=self.dtype)[0]
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def test_dynamic_scaler2tensor(self):
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paddle.disable_static()
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x = paddle.to_tensor(self.x_np)
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self.assertEqual(DTYPE_MAP[x.dtype], self.dtype)
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self.assertEqual(x.numpy(), self.x_np)
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if self.dtype in [
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np.bool_
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]: # bool is not supported convert to 0D-Tensor
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return
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self.assertEqual(len(x.shape), 0)
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def test_static_scaler2tensor(self):
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if self.dtype in [np.float16, np.complex64]:
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return
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paddle.enable_static()
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x = paddle.to_tensor(self.x_np)
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self.assertEqual(DTYPE_MAP[x.dtype], self.dtype)
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if self.dtype in [np.bool_, np.float64]:
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# bool is not supported convert to 0D-Tensor and float64 not supported in static mode
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return
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self.assertEqual(len(x.shape), 0)
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class NumpyScaler2TensorBool(NumpyScaler2Tensor):
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def setUp(self):
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self.dtype = np.bool_
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self.x_np = np.array([1], dtype=self.dtype)[0]
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class NumpyScaler2TensorFloat16(NumpyScaler2Tensor):
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def setUp(self):
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self.dtype = np.float16
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self.x_np = np.array([1], dtype=self.dtype)[0]
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class NumpyScaler2TensorFloat64(NumpyScaler2Tensor):
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def setUp(self):
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self.dtype = np.float64
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self.x_np = np.array([1], dtype=self.dtype)[0]
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class NumpyScaler2TensorInt32(NumpyScaler2Tensor):
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def setUp(self):
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self.dtype = np.int32
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self.x_np = np.array([1], dtype=self.dtype)[0]
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class NumpyScaler2TensorInt64(NumpyScaler2Tensor):
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def setUp(self):
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self.dtype = np.int64
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self.x_np = np.array([1], dtype=self.dtype)[0]
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class NumpyScaler2TensorComplex64(NumpyScaler2Tensor):
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def setUp(self):
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self.dtype = np.complex64
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self.x_np = np.array([1], dtype=self.dtype)[0]
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