# 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.
# ============================================================================
""" test nn ops """
import functools
import numpy as np
import mindspore.nn as nn
import mindspore.context as context
import mindspore.common.dtype as mstype

from mindspore import Tensor, Parameter
from mindspore.common.initializer import initializer
from mindspore.ops import Primitive
from mindspore.ops import composite as C
from mindspore.ops import operations as P
from mindspore.ops import functional as F
from mindspore.ops import prim_attr_register, PrimitiveWithInfer
from mindspore.ops.primitive import constexpr
from mindspore import context
context.set_context(mode=context.GRAPH_MODE, save_graphs=True)


def test_cast_op_attr():
    class CastNet(nn.Cell):
        def __init__(self):
            super(CastNet, self).__init__()
            self.cast = P.Cast()
        def construct(self, x, t):
            return self.cast(x, t)
    
    class CastTypeTest(nn.Cell):
        def __init__(self, net):
            super(CastTypeTest, self).__init__()
            self.net = net
            self.cast = P.Cast()
        def construct(self, x, y, z):
            cast_op = self.cast
            t1 = cast_op(x, mstype.float32)
            t2 = cast_op(y, mstype.int32)
            cast_net = self.net
            t3 = cast_net(x, mstype.float16)
            t4 = cast_net(y, mstype.int32)
            t5 = cast_net(z, mstype.float16)
            return (t1, t2, t3, t4, t5)
    net = CastTypeTest(CastNet())
    t1 = Tensor(np.ones([1,16,1,1918]).astype(np.int32))
    t2 = Tensor(np.ones([1,16,1,3840]).astype(np.float32))
    t3 = Tensor(np.ones([1,16,1,1918]).astype(np.int32))
    out = net(t1, t2, t3)
    assert out[0].asnumpy().dtype == np.float32
    assert out[1].asnumpy().dtype == np.int32
    assert out[2].asnumpy().dtype == np.float16
    assert out[3].asnumpy().dtype == np.int32
    assert out[4].asnumpy().dtype == np.float16