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188 lines
7.1 KiB
188 lines
7.1 KiB
# 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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from __future__ import print_function
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import unittest
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from paddle.fluid.framework import default_main_program, Program, convert_np_dtype_to_dtype_, in_dygraph_mode
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import paddle.fluid as fluid
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import paddle.fluid.layers as layers
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import paddle.fluid.core as core
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import numpy as np
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class TestVariable(unittest.TestCase):
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def test_np_dtype_convert(self):
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DT = core.VarDesc.VarType
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convert = convert_np_dtype_to_dtype_
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self.assertEqual(DT.FP32, convert(np.float32))
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self.assertEqual(DT.FP16, convert("float16"))
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self.assertEqual(DT.FP64, convert("float64"))
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self.assertEqual(DT.INT32, convert("int32"))
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self.assertEqual(DT.INT16, convert("int16"))
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self.assertEqual(DT.INT64, convert("int64"))
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self.assertEqual(DT.BOOL, convert("bool"))
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self.assertEqual(DT.INT8, convert("int8"))
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self.assertEqual(DT.UINT8, convert("uint8"))
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def test_var(self):
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b = default_main_program().current_block()
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w = b.create_var(
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dtype="float64", shape=[784, 100], lod_level=0, name="fc.w")
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self.assertNotEqual(str(w), "")
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self.assertEqual(core.VarDesc.VarType.FP64, w.dtype)
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self.assertEqual((784, 100), w.shape)
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self.assertEqual("fc.w", w.name)
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self.assertEqual(0, w.lod_level)
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w = b.create_var(name='fc.w')
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self.assertEqual(core.VarDesc.VarType.FP64, w.dtype)
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self.assertEqual((784, 100), w.shape)
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self.assertEqual("fc.w", w.name)
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self.assertEqual(0, w.lod_level)
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self.assertRaises(ValueError,
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lambda: b.create_var(name="fc.w", shape=(24, 100)))
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def test_step_scopes(self):
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prog = Program()
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b = prog.current_block()
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var = b.create_var(
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name='step_scopes', type=core.VarDesc.VarType.STEP_SCOPES)
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self.assertEqual(core.VarDesc.VarType.STEP_SCOPES, var.type)
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def _test_slice(self, place):
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b = default_main_program().current_block()
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w = b.create_var(dtype="float64", shape=[784, 100, 100], lod_level=0)
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for i in range(3):
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nw = w[i]
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self.assertEqual((100, 100), nw.shape)
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nw = w[:]
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self.assertEqual((784, 100, 100), nw.shape)
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nw = w[:, :]
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self.assertEqual((784, 100, 100), nw.shape)
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nw = w[:, :, -1]
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self.assertEqual((784, 100), nw.shape)
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nw = w[1, 1, 1]
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self.assertEqual(len(nw.shape), 1)
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self.assertEqual(nw.shape[0], 1)
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nw = w[:, :, :-1]
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self.assertEqual((784, 100, 99), nw.shape)
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self.assertEqual(0, nw.lod_level)
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main = fluid.Program()
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with fluid.program_guard(main):
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exe = fluid.Executor(place)
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tensor_array = np.array(
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[[[1, 2, 3], [4, 5, 6], [7, 8, 9]],
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[[10, 11, 12], [13, 14, 15], [16, 17, 18]],
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[[19, 20, 21], [22, 23, 24], [25, 26, 27]]]).astype('float32')
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var = fluid.layers.assign(tensor_array)
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var1 = var[0, 1, 1]
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var2 = var[1:]
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var3 = var[0:1]
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var4 = var[::-1]
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var5 = var[1, 1:, 1:]
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var_reshape = fluid.layers.reshape(var, [3, -1, 3])
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var6 = var_reshape[:, :, -1]
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var7 = var[:, :, :-1]
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var8 = var[:1, :1, :1]
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var9 = var[:-1, :-1, :-1]
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var10 = var[::-1, :1, :-1]
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var11 = var[:-1, ::-1, -1:]
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var12 = var[1:2, 2:, ::-1]
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var13 = var[2:10, 2:, -2:-1]
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var14 = var[1:-1, 0:2, ::-1]
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var15 = var[::-1, ::-1, ::-1]
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x = fluid.layers.data(name='x', shape=[13], dtype='float32')
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y = fluid.layers.fc(input=x, size=1, act=None)
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y_1 = y[:, 0]
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feeder = fluid.DataFeeder(place=place, feed_list=[x])
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data = []
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data.append((np.random.randint(10, size=[13]).astype('float32')))
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exe.run(fluid.default_startup_program())
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local_out = exe.run(main,
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feed=feeder.feed([data]),
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fetch_list=[
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var, var1, var2, var3, var4, var5, var6,
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var7, var8, var9, var10, var11, var12,
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var13, var14, var15
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])
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self.assertTrue(
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np.array_equal(local_out[1], tensor_array[0, 1, 1:2]))
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self.assertTrue(np.array_equal(local_out[2], tensor_array[1:]))
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self.assertTrue(np.array_equal(local_out[3], tensor_array[0:1]))
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self.assertTrue(np.array_equal(local_out[4], tensor_array[::-1]))
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self.assertTrue(
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np.array_equal(local_out[5], tensor_array[1, 1:, 1:]))
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self.assertTrue(
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np.array_equal(local_out[6],
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tensor_array.reshape((3, -1, 3))[:, :, -1]))
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self.assertTrue(
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np.array_equal(local_out[7], tensor_array[:, :, :-1]))
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self.assertTrue(
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np.array_equal(local_out[8], tensor_array[:1, :1, :1]))
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self.assertTrue(
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np.array_equal(local_out[9], tensor_array[:-1, :-1, :-1]))
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self.assertTrue(
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np.array_equal(local_out[10], tensor_array[::-1, :1, :-1]))
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self.assertTrue(
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np.array_equal(local_out[11], tensor_array[:-1, ::-1, -1:]))
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self.assertTrue(
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np.array_equal(local_out[12], tensor_array[1:2, 2:, ::-1]))
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self.assertTrue(
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np.array_equal(local_out[13], tensor_array[2:10, 2:, -2:-1]))
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self.assertTrue(
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np.array_equal(local_out[14], tensor_array[1:-1, 0:2, ::-1]))
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self.assertTrue(
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np.array_equal(local_out[15], tensor_array[::-1, ::-1, ::-1]))
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def test_slice(self):
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place = fluid.CPUPlace()
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self._test_slice(place)
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if core.is_compiled_with_cuda():
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self._test_slice(core.CUDAPlace(0))
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def _tostring(self):
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b = default_main_program().current_block()
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w = b.create_var(dtype="float64", lod_level=0)
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self.assertTrue(isinstance(str(w), str))
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if core.is_compiled_with_cuda():
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wc = b.create_var(dtype="int", lod_level=0)
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self.assertTrue(isinstance(str(wc), str))
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def test_tostring(self):
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with fluid.dygraph.guard():
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self._tostring()
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with fluid.program_guard(default_main_program()):
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self._tostring()
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if __name__ == '__main__':
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unittest.main()
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