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#include "caffe2/operators/given_tensor_fill_op.h"
namespace caffe2 {
REGISTER_CPU_OPERATOR(GivenTensorFill, GivenTensorFillOp<float, CPUContext>);
REGISTER_CPU_OPERATOR(
GivenTensorDoubleFill,
GivenTensorFillOp<double, CPUContext>);
REGISTER_CPU_OPERATOR(GivenTensorBoolFill, GivenTensorFillOp<bool, CPUContext>);
REGISTER_CPU_OPERATOR(
GivenTensorInt16Fill,
GivenTensorFillOp<int16_t, CPUContext>);
REGISTER_CPU_OPERATOR(GivenTensorIntFill, GivenTensorFillOp<int, CPUContext>);
REGISTER_CPU_OPERATOR(
GivenTensorInt64Fill,
GivenTensorFillOp<int64_t, CPUContext>);
REGISTER_CPU_OPERATOR(
GivenTensorStringFill,
GivenTensorFillOp<std::string, CPUContext>);
NO_GRADIENT(GivenTensorFill);
NO_GRADIENT(GivenTensorDoubleFill);
NO_GRADIENT(GivenTensorBoolFill);
NO_GRADIENT(GivenTensorInt16Fill);
NO_GRADIENT(GivenTensorIntFill);
NO_GRADIENT(GivenTensorInt64Fill);
NO_GRADIENT(GivenTensorStringFill);
OPERATOR_SCHEMA(GivenTensorFill)
.NumInputs(0, 1)
.NumOutputs(1)
.AllowInplace({{0, 0}})
.SetDoc(R"DOC(
This op fills an output tensor with the data specified by the *value* and *dtype* arguments. The output tensor shape is specified by the *shape* argument. Beware, when using this argument *value* should have a value for every element of the *output*, as missing values will not be initialized automatically. If *input_as_shape* is set to *true*, then the *input* should be a 1D tensor containing the desired output shape (the dimensions specified in *extra_shape* will also be appended). In this case, the *shape* argument should **not** be set.
*Note: Do not set the shape argument and pass in an input at the same time.*
Github Links:
- https://github.com/caffe2/caffe2/blob/master/caffe2/operators/given_tensor_fill_op.h
- https://github.com/caffe2/caffe2/blob/master/caffe2/operators/given_tensor_fill_op.cc
<details>
<summary> <b>Example</b> </summary>
**Code**
```
workspace.ResetWorkspace()
op = core.CreateOperator(
"GivenTensorFill",
[],
["out"],
values=[1., 2., 3.],
shape=[3],
)
workspace.RunOperatorOnce(op)
print("Out:\n", workspace.FetchBlob("out"))
```
**Result**
```
Out:
[1. 2. 3.]
```
</details>
)DOC")
.Arg(
"values",
"*(type depends on dtype, Required=True)* The value of the elements to go in the *output* tensor.",
true /* required */)
.Arg(
"dtype",
"The data type for the elements of the output tensor. Strictly must be one of the types from DataType enum in TensorProto.")
.Arg(
"shape",
"*(type: [int])* Desired shape of the *output* tensor.")
.Arg(
"extra_shape",
"*(type: [int])* The additional dimensions appended at the end of the *shape* indicated by the input blob. Cannot set the *extra_shape* argument when there is no input blob.")
.Arg(
"input_as_shape",
"*(type: bool; default: False)* set to *True* to use the *input* as shape. First, input must be in CPU context.")
.Input(
0,
"input",
"(Optional) 1D tensor specifying the shape of the output. Must be used with *input_as_shape=True*")
.Output(
0,
"output",
"Output tensor with desired dimension filled with specified data. If the shape argument is set, this is the shape specified, and if the *input* exists and *input_as_shape=True*, it is the shape specified by the *input* tensor.")
.TensorInferenceFunction(FillerTensorInference<>);
OPERATOR_SCHEMA(GivenTensorDoubleFill)
.NumInputs(0, 1)
.NumOutputs(1)
.AllowInplace({{0, 0}})
.Arg(
"values",
"The value for the elements of the output tensor.",
true /* required */)
.Arg(
"shape",
"The shape of the output tensor."
"Cannot set the shape argument and pass in an input at the same time.")
.Arg(
"extra_shape",
"The additional dimensions appended at the end of the shape indicated"
"by the input blob."
"Cannot set the extra_shape argument when there is no input blob.")
.Arg(
"input_as_shape",
"1D tensor containing the desired output shape. First input must be in CPU context.")
.TensorInferenceFunction(
FillerTensorInference<TensorProto_DataType_DOUBLE>);
OPERATOR_SCHEMA(GivenTensorBoolFill)
.NumInputs(0, 1)
.NumOutputs(1)
.AllowInplace({{0, 0}})
.Arg(
"values",
"The value for the elements of the output tensor.",
true /* required */)
.Arg(
"shape",
"The shape of the output tensor."
"Cannot set the shape argument and pass in an input at the same time.")
.Arg(
"extra_shape",
"The additional dimensions appended at the end of the shape indicated"
"by the input blob."
"Cannot set the extra_shape argument when there is no input blob.")
.Arg(
"input_as_shape",
"1D tensor containing the desired output shape. First input must be in CPU context.")
.TensorInferenceFunction(FillerTensorInference<TensorProto_DataType_BOOL>);
OPERATOR_SCHEMA(GivenTensorInt16Fill)
.NumInputs(0, 1)
.NumOutputs(1)
.AllowInplace({{0, 0}})
.Arg(
"values",
"The value for the elements of the output tensor.",
true /* required */)
.Arg(
"shape",
"The shape of the output tensor."
"Cannot set the shape argument and pass in an input at the same time.")
.Arg(
"extra_shape",
"The additional dimensions appended at the end of the shape indicated"
"by the input blob."
"Cannot set the extra_shape argument when there is no input blob.")
.Arg(
"input_as_shape",
"1D tensor containing the desired output shape. First input must be in CPU context.")
.TensorInferenceFunction(FillerTensorInference<TensorProto_DataType_INT16>);
OPERATOR_SCHEMA(GivenTensorIntFill)
.NumInputs(0, 1)
.NumOutputs(1)
.AllowInplace({{0, 0}})
.Arg(
"values",
"The value for the elements of the output tensor.",
true /* required */)
.Arg(
"shape",
"The shape of the output tensor."
"Cannot set the shape argument and pass in an input at the same time.")
.Arg(
"extra_shape",
"The additional dimensions appended at the end of the shape indicated"
"by the input blob."
"Cannot set the extra_shape argument when there is no input blob.")
.Arg(
"input_as_shape",
"1D tensor containing the desired output shape. First input must be in CPU context.")
.TensorInferenceFunction(FillerTensorInference<TensorProto_DataType_INT32>);
OPERATOR_SCHEMA(GivenTensorInt64Fill)
.NumInputs(0, 1)
.NumOutputs(1)
.AllowInplace({{0, 0}})
.Arg(
"values",
"The value for the elements of the output tensor.",
true /* required */)
.Arg(
"shape",
"The shape of the output tensor."
"Cannot set the shape argument and pass in an input at the same time.")
.Arg(
"extra_shape",
"The additional dimensions appended at the end of the shape indicated"
"by the input blob."
"Cannot set the extra_shape argument when there is no input blob.")
.Arg(
"input_as_shape",
"1D tensor containing the desired output shape. First input must be in CPU context.")
.TensorInferenceFunction(FillerTensorInference<TensorProto_DataType_INT64>);
OPERATOR_SCHEMA(GivenTensorStringFill)
.NumInputs(0, 1)
.NumOutputs(1)
.AllowInplace({{0, 0}})
.Arg(
"values",
"The value for the elements of the output tensor.",
true /* required */)
.Arg(
"shape",
"The shape of the output tensor."
"Cannot set the shape argument and pass in an input at the same time.")
.Arg(
"extra_shape",
"The additional dimensions appended at the end of the shape indicated"
"by the input blob."
"Cannot set the extra_shape argument when there is no input blob.")
.Arg(
"input_as_shape",
"1D tensor containing the desired output shape. First input must be in CPU context.")
.TensorInferenceFunction(
FillerTensorInference<TensorProto_DataType_STRING>);
} // namespace caffe2
|
