forked from mindspore-Ecosystem/mindspore
77 lines
2.7 KiB
Python
77 lines
2.7 KiB
Python
# Copyright 2020 Huawei Technologies Co., Ltd
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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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# ============================================================================
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""" test_pynative_embeddinglookup """
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import pytest
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import numpy as np
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import mindspore.ops.operations as op
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from mindspore import Tensor, context
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from mindspore.nn import Cell
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def setup_module():
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context.set_context(mode=context.PYNATIVE_MODE, device_target="Ascend")
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class MetaFactory:
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def __init__(self):
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self.device_target = context.get_context('device_target')
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self.rank_size = None
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self.device_id = None
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self.global_rank_id = None
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class OpsFactory(MetaFactory):
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def __init__(self, dtype=np.float16):
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super().__init__()
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self.dtype = dtype
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if self.dtype == np.float16:
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self.loss = 1e-3
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elif self.dtype == np.float32:
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self.loss = 1e-4
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elif self.dtype == np.float64:
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self.loss = 1e-5
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else:
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self.loss = 0
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class EmbeddingLookup(Cell):
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def __init__(self, offset):
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super().__init__()
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self.op = op.EmbeddingLookup()
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self.offset = offset
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def construct(self, params, indices):
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x = self.op(params, indices, self.offset)
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return x
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class EmbeddingLookupFactory(OpsFactory):
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def __init__(self, params_shape, indices_shape, offset=0, low=0, high=2, dtype=np.float32, ids_type=np.int32):
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super().__init__(dtype=dtype)
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self.input_np = np.random.randn(*params_shape).astype(dtype)
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self.indices_np = np.random.randint(low, high, size=indices_shape).astype(ids_type)
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self.offset = offset
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self.output_grad_np = None
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def forward_mindspore_impl(self):
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net = EmbeddingLookup(self.offset)
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out = net(Tensor(self.input_np), Tensor(self.indices_np))
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return out.asnumpy()
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@pytest.mark.level0
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.env_onecard
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def test_embeddinglookup_indices_outrange():
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fact = EmbeddingLookupFactory(params_shape=(2, 4), indices_shape=(2, 3), low=1, high=3, offset=10, dtype=np.int8)
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out = fact.forward_mindspore_impl()
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out_expect = np.zeros((2, 3, 4))
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np.allclose(out_expect, out)
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