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Use single file than multiple files
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‎paddle/fluid/operators/reshape_op.cc

Lines changed: 164 additions & 52 deletions
Original file line numberDiff line numberDiff line change
@@ -12,14 +12,108 @@ 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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#include "paddle/fluid/operators/reshape_op.h"
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#include <string>
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#include <vector>
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#include "paddle/fluid/framework/op_registry.h"
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namespace paddle {
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namespace operators {
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class ReshapeOp : public framework::OperatorWithKernel {
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public:
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ReshapeOp(const std::string &type, const framework::VariableNameMap &inputs,
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const framework::VariableNameMap &outputs,
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const framework::AttributeMap &attrs)
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: OperatorWithKernel(type, inputs, outputs, attrs) {}
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29+
void InferShape(framework::InferShapeContext *ctx) const override {
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PADDLE_ENFORCE(ctx->HasInput("X"),
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"Input(X) of ReshapeOp should not be null.");
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PADDLE_ENFORCE(ctx->HasOutput("Out"),
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"Output(Out) of ReshapeOp should not be null.");
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const std::vector<int> &shape = ctx->Attrs().Get<std::vector<int>>("shape");
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PADDLE_ENFORCE(!shape.empty(),
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"The shape information must be set by Attr(shape).");
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39+
if (ctx->HasInput("Shape") && ctx->IsRuntime()) {
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// If true, set the shape of Output(Out) according to Input(Shape) in
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// ReshapeKernel with ExecutionContext. Also check LoD in ReshapeKernel.
42+
ctx->ShareLoD("X", /*->*/ "Out");
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return;
44+
}
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auto x_dims = ctx->GetInputDim("X");
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auto out_dims = ValidateShape(shape, x_dims);
48+
ctx->SetOutputDim("Out", out_dims);
49+
if (x_dims[0] == out_dims[0]) {
50+
// Only pass LoD when the first dimension of output and Input(X)
51+
// are the same.
52+
ctx->ShareLoD("X", /*->*/ "Out");
53+
}
54+
}
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56+
static framework::DDim ValidateShape(const std::vector<int> shape,
57+
const framework::DDim &in_dims) {
58+
const int64_t in_size = framework::product(in_dims);
59+
// only one dimension can be set to -1, whose size will be automatically
60+
// infered.
61+
const int64_t unk_dim_val = -1;
62+
const int64_t copy_dim_val = 0;
63+
64+
std::vector<int64_t> output_shape(shape.size(), 0);
65+
int64_t capacity = 1;
66+
int unk_dim_idx = -1;
67+
for (size_t i = 0; i < shape.size(); ++i) {
68+
if (shape[i] == unk_dim_val) {
69+
PADDLE_ENFORCE(
70+
unk_dim_idx == -1,
71+
"Only one input dimension of Attr(shape) can be unknown.");
72+
unk_dim_idx = i;
73+
} else if (shape[i] == copy_dim_val) {
74+
PADDLE_ENFORCE(
75+
static_cast<int>(i) < in_dims.size(),
76+
"The index of dimension to copy from input shape must be less "
77+
"than the size of input shape.");
78+
} else {
79+
PADDLE_ENFORCE(
80+
shape[i] > 0,
81+
"Each input dimension of Attr(shape) must not be negtive except "
82+
"one unknown dimension.");
83+
}
84+
85+
capacity *= (shape[i] ? shape[i] : in_dims[i]);
86+
output_shape[i] =
87+
(shape[i] ? static_cast<int64_t>(shape[i]) : in_dims[i]);
88+
}
89+
90+
if (unk_dim_idx != -1) {
91+
if (in_size > 0) {
92+
// in_size < 0 and is un-determinate in compile time, skip the check,
93+
// for example, in_dims = [-1, 8, 1, 1], shape = [-1, 3, 8],
94+
// capacity = -24, in_size = -8, output_shape[0] = 0
95+
// the following check will fail.
96+
output_shape[unk_dim_idx] = -in_size / capacity;
97+
PADDLE_ENFORCE_EQ(output_shape[unk_dim_idx] * capacity, -in_size,
98+
"Invalid shape is given.");
99+
} else {
100+
output_shape[unk_dim_idx] = -1;
101+
}
102+
} else {
103+
PADDLE_ENFORCE_EQ(capacity, in_size, "Invalid shape is given.");
104+
}
105+
return framework::make_ddim(output_shape);
106+
}
107+
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protected:
109+
framework::OpKernelType GetExpectedKernelType(
110+
const framework::ExecutionContext &ctx) const override {
111+
return framework::OpKernelType(
112+
framework::ToDataType(ctx.Input<framework::LoDTensor>("X")->type()),
113+
ctx.device_context());
114+
}
115+
};
116+
23117
class ReshapeOpMaker : public framework::OpProtoAndCheckerMaker {
24118
public:
25119
void Make() override {
@@ -107,64 +201,72 @@ class ReshapeGradOp : public framework::OperatorWithKernel {
107201
}
108202
};
109203

110-
void ReshapeKernel::operator()(const framework::ExecutionContext &ctx) const {
111-
auto *out = ctx.Output<framework::LoDTensor>("Out");
112-
auto *in = ctx.Input<framework::LoDTensor>("X");
204+
class ReshapeKernel {
205+
public:
206+
void operator()(const framework::ExecutionContext &ctx) const {
207+
auto *out = ctx.Output<framework::LoDTensor>("Out");
208+
auto *in = ctx.Input<framework::LoDTensor>("X");
113209

114-
auto *shape_tensor = ctx.HasInput("Shape")
115-
? ctx.Input<framework::LoDTensor>("Shape")
116-
: nullptr;
210+
auto *shape_tensor = ctx.HasInput("Shape")
211+
? ctx.Input<framework::LoDTensor>("Shape")
212+
: nullptr;
117213

118-
framework::DDim out_dims = out->dims();
214+
framework::DDim out_dims = out->dims();
119215

120-
if (shape_tensor) {
121-
auto *shape_data = shape_tensor->data<int>();
122-
framework::Tensor cpu_shape_tensor;
123-
if (platform::is_gpu_place(ctx.GetPlace())) {
124-
TensorCopySync(*shape_tensor, platform::CPUPlace(), &cpu_shape_tensor);
125-
shape_data = cpu_shape_tensor.data<int>();
216+
if (shape_tensor) {
217+
auto *shape_data = shape_tensor->data<int>();
218+
framework::Tensor cpu_shape_tensor;
219+
if (platform::is_gpu_place(ctx.GetPlace())) {
220+
TensorCopySync(*shape_tensor, platform::CPUPlace(), &cpu_shape_tensor);
221+
shape_data = cpu_shape_tensor.data<int>();
222+
}
223+
auto shape =
224+
std::vector<int>(shape_data, shape_data + shape_tensor->numel());
225+
out_dims = ReshapeOp::ValidateShape(shape, in->dims());
226+
}
227+
if (!in->lod().empty()) {
228+
PADDLE_ENFORCE_EQ(
229+
out_dims[0], in->dims()[0],
230+
"Reshape operator cannot reshape an input sequence batch "
231+
"into an output sequence batch that has a different "
232+
"number of time steps. Please consider using "
233+
"sequence_reshape op.");
126234
}
127-
auto shape =
128-
std::vector<int>(shape_data, shape_data + shape_tensor->numel());
129-
out_dims = ReshapeOp::ValidateShape(shape, in->dims());
130-
}
131-
if (!in->lod().empty()) {
132-
PADDLE_ENFORCE_EQ(out_dims[0], in->dims()[0],
133-
"Reshape operator cannot reshape an input sequence batch "
134-
"into an output sequence batch that has a different "
135-
"number of time steps. Please consider using "
136-
"sequence_reshape op.");
137-
}
138235

139-
bool inplace = ctx.Attr<bool>("inplace");
140-
out->Resize(out_dims);
141-
if (!inplace) {
142-
out->mutable_data(ctx.GetPlace(), in->type());
143-
framework::TensorCopySync(*in, ctx.GetPlace(), out);
144-
out->Resize(out_dims);
145-
} else {
146-
out->ShareDataWith(*in);
236+
bool inplace = ctx.Attr<bool>("inplace");
147237
out->Resize(out_dims);
238+
if (!inplace) {
239+
out->mutable_data(ctx.GetPlace(), in->type());
240+
framework::TensorCopySync(*in, ctx.GetPlace(), out);
241+
out->Resize(out_dims);
242+
} else {
243+
out->ShareDataWith(*in);
244+
out->Resize(out_dims);
245+
}
148246
}
149-
}
150-
void ReshapeGradKernel::operator()(
151-
const framework::ExecutionContext &ctx) const {
152-
auto *d_out = ctx.Input<framework::Tensor>(framework::GradVarName("Out"));
153-
auto *d_x = ctx.Output<framework::Tensor>(framework::GradVarName("X"));
154-
155-
d_x->mutable_data(ctx.GetPlace(), d_out->type());
156-
bool inplace = ctx.Attr<bool>("inplace");
157-
158-
auto in_dims = d_x->dims();
159-
if (!inplace) {
160-
framework::TensorCopy(*d_out, ctx.GetPlace(), ctx.device_context(), d_x);
161-
ctx.device_context().Wait();
162-
d_x->Resize(in_dims);
163-
} else {
164-
d_x->ShareDataWith(*d_out);
165-
d_x->Resize(in_dims);
247+
};
248+
249+
class ReshapeGradKernel {
250+
public:
251+
void operator()(const framework::ExecutionContext &ctx) const {
252+
auto *d_out = ctx.Input<framework::Tensor>(framework::GradVarName("Out"));
253+
auto *d_x = ctx.Output<framework::Tensor>(framework::GradVarName("X"));
254+
255+
d_x->mutable_data(ctx.GetPlace(), d_out->type());
256+
bool inplace = ctx.Attr<bool>("inplace");
257+
258+
auto in_dims = d_x->dims();
259+
if (!inplace) {
260+
framework::TensorCopy(*d_out, ctx.GetPlace(), ctx.device_context(), d_x);
261+
ctx.device_context().Wait();
262+
d_x->Resize(in_dims);
263+
} else {
264+
d_x->ShareDataWith(*d_out);
265+
d_x->Resize(in_dims);
266+
}
166267
}
167-
}
268+
};
269+
168270
} // namespace operators
169271
} // namespace paddle
170272
namespace ops = paddle::operators;
@@ -179,3 +281,13 @@ REGISTER_OP_CPU_KERNEL_FUNCTOR(reshape_grad, float, ops::ReshapeGradKernel,
179281
double, ops::ReshapeGradKernel, int,
180282
ops::ReshapeGradKernel, int64_t,
181283
ops::ReshapeGradKernel);
284+
285+
#ifdef PADDLE_WITH_CUDA
286+
REGISTER_OP_CUDA_KERNEL_FUNCTOR(reshape, float, ops::ReshapeKernel, double,
287+
ops::ReshapeKernel, int, ops::ReshapeKernel,
288+
int64_t, ops::ReshapeKernel);
289+
REGISTER_OP_CUDA_KERNEL_FUNCTOR(reshape_grad, float, ops::ReshapeGradKernel,
290+
double, ops::ReshapeGradKernel, int,
291+
ops::ReshapeGradKernel, int64_t,
292+
ops::ReshapeGradKernel);
293+
#endif

‎paddle/fluid/operators/reshape_op.cu.cc

Lines changed: 0 additions & 24 deletions
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