# Copyright 2020 Huawei Technologies Co., Ltd # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================ """multitype_ops directory test case""" import numpy as np import pytest import mindspore.nn as nn from mindspore import Tensor from mindspore import dtype as mstype from mindspore.ops import functional as F import mindspore.context as context class TensorIntAutoCast(nn.Cell): def __init__(self,): super(TensorIntAutoCast, self).__init__() self.i = 2 def construct(self, t): z = F.tensor_mul(t, self.i) return z class TensorFPAutoCast(nn.Cell): def __init__(self,): super(TensorFPAutoCast, self).__init__() self.f = 1.2 def construct(self, t): z = F.tensor_mul(t, self.f) return z class TensorBoolAutoCast(nn.Cell): def __init__(self,): super(TensorBoolAutoCast, self).__init__() self.f = True def construct(self, t): z = F.tensor_mul(t, self.f) return z class TensorAutoCast(nn.Cell): def __init__(self,): super(TensorAutoCast, self).__init__() def construct(self, t1, t2): z = F.tensor_mul(t1, t2) return z def test_tensor_auto_cast(): context.set_context(mode=context.GRAPH_MODE) Tensor([True, False], mstype.bool_) t_uint8 = Tensor(np.ones([2, 1, 2, 2]), mstype.uint8) t_int8 = Tensor(np.ones([2, 1, 2, 2]), mstype.int8) t_int16 = Tensor(np.ones([2, 1, 2, 2]), mstype.int16) t_int32 = Tensor(np.ones([2, 1, 2, 2]), mstype.int32) t_int64 = Tensor(np.ones([2, 1, 2, 2]), mstype.int64) t_fp16 = Tensor(np.ones([2, 1, 2, 2]), mstype.float16) t_fp32 = Tensor(np.ones([2, 1, 2, 2]), mstype.float32) t_fp64 = Tensor(np.ones([2, 1, 2, 2]), mstype.float64) net = TensorAutoCast() rs = net(t_uint8, t_int8) assert rs.dtype == mstype.int16 rs = net(t_uint8, t_int16) assert rs.dtype == mstype.int16 rs = net(t_uint8, t_int32) assert rs.dtype == mstype.int32 rs = net(t_uint8, t_int64) assert rs.dtype == mstype.int64 rs = net(t_int8, t_int16) assert rs.dtype == mstype.int16 rs = net(t_int8, t_int32) assert rs.dtype == mstype.int32 rs = net(t_int8, t_int64) assert rs.dtype == mstype.int64 rs = net(t_int16, t_int32) assert rs.dtype == mstype.int32 rs = net(t_int16, t_int64) assert rs.dtype == mstype.int64 rs = net(t_int32, t_int64) assert rs.dtype == mstype.int64 rs = net(t_fp16, t_fp32) assert rs.dtype == mstype.float32 rs = net(t_fp16, t_fp64) assert rs.dtype == mstype.float64 rs = net(t_fp32, t_fp64) assert rs.dtype == mstype.float64 rs = net(t_uint8, t_fp16) assert rs.dtype == mstype.float16 rs = net(t_uint8, t_fp32) assert rs.dtype == mstype.float32 rs = net(t_uint8, t_fp64) assert rs.dtype == mstype.float64 rs = net(t_int8, t_fp64) assert rs.dtype == mstype.float64 rs = net(t_int16, t_fp64) assert rs.dtype == mstype.float64 rs = net(t_int32, t_fp64) assert rs.dtype == mstype.float64 rs = net(t_int64, t_fp64) assert rs.dtype == mstype.float64 rs = net(t_fp16, t_int8) assert rs.dtype == mstype.float16 rs = net(t_fp16, t_uint8) assert rs.dtype == mstype.float16 rs = net(t_fp16, t_int16) assert rs.dtype == mstype.float16 rs = net(t_fp16, t_int32) assert rs.dtype == mstype.float16 rs = net(t_fp16, t_int64) assert rs.dtype == mstype.float16 tint = TensorIntAutoCast() rs = tint(t_uint8) assert rs.dtype == mstype.uint8 rs = tint(t_int8) assert rs.dtype == mstype.int8 rs = tint(t_int16) assert rs.dtype == mstype.int16 rs = tint(t_int32) assert rs.dtype == mstype.int32 rs = tint(t_int64) assert rs.dtype == mstype.int64 rs = tint(t_fp16) assert rs.dtype == mstype.float16 rs = tint(t_fp32) assert rs.dtype == mstype.float32 rs = tint(t_fp64) assert rs.dtype == mstype.float64 tfp = TensorFPAutoCast() rs = tfp(t_uint8) assert rs.dtype == mstype.float32 rs = tfp(t_int8) assert rs.dtype == mstype.float32 rs = tfp(t_int16) assert rs.dtype == mstype.float32 rs = tfp(t_int32) assert rs.dtype == mstype.float32 rs = tfp(t_int64) assert rs.dtype == mstype.float32 rs = tfp(t_fp16) assert rs.dtype == mstype.float32 rs = tfp(t_fp32) assert rs.dtype == mstype.float32 rs = tfp(t_fp64) assert rs.dtype == mstype.float64 t_uint16 = Tensor(np.ones([2, 1, 2, 2]), mstype.uint16) t_uint32 = Tensor(np.ones([2, 1, 2, 2]), mstype.uint32) t_uint64 = Tensor(np.ones([2, 1, 2, 2]), mstype.uint64) with pytest.raises(TypeError): net(t_uint16, t_uint8) with pytest.raises(TypeError): net(t_uint16, t_int8) with pytest.raises(TypeError): net(t_uint16, t_int16) with pytest.raises(TypeError): net(t_uint16, t_int32) with pytest.raises(TypeError): net(t_uint16, t_int64) with pytest.raises(TypeError): net(t_uint32, t_uint8) with pytest.raises(TypeError): net(t_uint32, t_int8) with pytest.raises(TypeError): net(t_uint32, t_int16) with pytest.raises(TypeError): net(t_uint32, t_int32) with pytest.raises(TypeError): net(t_uint32, t_int64) with pytest.raises(TypeError): net(t_uint64, t_uint8) with pytest.raises(TypeError): net(t_uint64, t_int8) with pytest.raises(TypeError): net(t_uint64, t_int16) with pytest.raises(TypeError): net(t_uint64, t_int32) with pytest.raises(TypeError): net(t_uint64, t_int64) with pytest.raises(TypeError): net(t_uint16, t_fp16) with pytest.raises(TypeError): net(t_uint16, t_fp32) with pytest.raises(TypeError): net(t_uint16, t_fp64) with pytest.raises(TypeError): net(t_uint32, t_fp16) with pytest.raises(TypeError): net(t_uint32, t_fp32) with pytest.raises(TypeError): net(t_uint32, t_fp64) with pytest.raises(TypeError): net(t_uint64, t_fp16) with pytest.raises(TypeError): net(t_uint64, t_fp32) with pytest.raises(TypeError): net(t_uint64, t_fp64) with pytest.raises(TypeError): tfp(t_uint16) with pytest.raises(TypeError): tfp(t_uint32) with pytest.raises(TypeError): tfp(t_uint64) with pytest.raises(TypeError): tint(t_uint16) with pytest.raises(TypeError): tint(t_uint32) with pytest.raises(TypeError): tint(t_uint64) bnet = TensorBoolAutoCast() with pytest.raises(TypeError): bnet(t_uint8) with pytest.raises(TypeError): bnet(t_int8) with pytest.raises(TypeError): bnet(t_int16) with pytest.raises(TypeError): bnet(t_int32) with pytest.raises(TypeError): bnet(t_int64) with pytest.raises(TypeError): bnet(t_fp16) with pytest.raises(TypeError): bnet(t_fp32) with pytest.raises(TypeError): bnet(t_fp64) def test_bool_tensor_and_float(): context.set_context(mode=context.GRAPH_MODE) t_bool = Tensor(np.ones([2, 1, 2, 2]).astype(np.bool), mstype.bool_) t_int32 = Tensor(np.ones([2, 1, 2, 2]), mstype.int32) t_fp16 = Tensor(np.ones([2, 1, 2, 2]), mstype.float16) t_fp32 = Tensor(np.ones([2, 1, 2, 2]), mstype.float32) net = TensorFPAutoCast() out = net(t_bool) assert out.dtype == mstype.float32 net = TensorIntAutoCast() out = net(t_bool) assert out.dtype == mstype.int32 out = net(t_fp16) assert out.dtype == mstype.float16 out = net(t_fp32) assert out.dtype == mstype.float32 out = net(t_int32) assert out.dtype == mstype.int32