!8579 Add view function for tensor

From: @liangzhibo
Reviewed-by: @zh_qh,@chenfei52
Signed-off-by: @zh_qh
pull/8579/MERGE
mindspore-ci-bot 4 years ago committed by Gitee
commit a321f402c8

@ -28,6 +28,7 @@ __all__ = ['MultitypeFuncGraph', 'env_get', 'hyper_add', 'zeros_like', 'ones_lik
trans = P.Transpose()
shape_ = P.Shape()
reshape_ = P.Reshape()
dtype_ = P.DType()
def all_(x, axis=(), keep_dims=False):
@ -162,6 +163,12 @@ def expand_tensor_as(x, y):
return broadcast_to(x)
def view(x, *shape):
"""Reshape tensor, if shape is -1, reshape tensor into one dimension"""
shape = check_view_shape(shape)
return reshape_(x, shape)
def isinstance_(x, base_type):
"""Determine whether x is an instance of base_type."""
x_type = F.typeof(x)
@ -232,6 +239,18 @@ def const_tensor_to_bool(x):
raise ValueError("The truth value of an array with several elements is ambiguous.")
@constexpr
def check_view_shape(x):
"""Check view function input shape"""
if not x:
raise ValueError("The shape variable should not be empty")
if isinstance(x[0], tuple):
if len(x) != 1:
raise ValueError(f"Only one tuple is needed, but got {x}")
x = x[0]
return x
def tensor_bool(x):
"""tensor as conditon, if is constant, return immediate bool value"""
is_cond = check_is_tensor_bool_cond(F.shape(x))

@ -167,6 +167,7 @@ BuiltInTypeMap &GetMethodMap() {
{"__le__", std::string("le")}, // C.le
{"__ge__", std::string("ge")}, // C.ge
{"expand_as", std::string("expand_tensor_as")}, // C.expand_as
{"view", std::string("view")}, // C.view
{"__matmul__", prim::kPrimDot}, // P.dot,
{"__len__", prim::kPrimArrayLen}, // P.array_len,
{"__getitem__", prim::kPrimArrayGetItem}, // P.array_getitem,

@ -0,0 +1,127 @@
# 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 view"""
import pytest
import mindspore.nn as nn
from mindspore import Tensor
from mindspore import context
context.set_context(mode=context.GRAPH_MODE)
def test_view():
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.value = Tensor([[1, 2, 3], [4, 5, 6]])
def construct(self):
return self.value.view(-1)
net = Net()
net()
def test_view_1():
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.value = Tensor([[1, 2, 3], [4, 5, 6]])
def construct(self):
return self.value.view((3, 2))
net = Net()
net()
def test_view_2():
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.value = Tensor([[1, 2, 3], [4, 5, 6]])
def construct(self):
return self.value.view(3, 2)
net = Net()
net()
def test_view_parameter():
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
def construct(self, x):
return x.view(-1)
net = Net()
net(Tensor([[1, 2, 3], [4, 5, 6]]))
def test_view_parameter_1():
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
def construct(self, x):
return x.view((3, 2))
net = Net()
net(Tensor([[1, 2, 3], [4, 5, 6]]))
def test_view_parameter_2():
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
def construct(self, x):
return x.view(3, 2)
net = Net()
net(Tensor([[1, 2, 3], [4, 5, 6]]))
def test_view_shape_error():
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.value = Tensor([[1, 2, 3], [4, 5, 6]])
def construct(self):
return self.value.view()
net = Net()
with pytest.raises(ValueError) as ex:
net()
assert "The shape variable should not be empty" in str(ex.value)
def test_view_shape_error_1():
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.value = Tensor([[1, 2, 3], [4, 5, 6]])
def construct(self):
return self.value.view((2, 3), (4, 5))
net = Net()
with pytest.raises(ValueError) as ex:
net()
assert "Only one tuple is needed" in str(ex.value)
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