pytorch/caffe2/queue/queue_ops.cc
Henry Lu 32b13d6243 Add linter for enforcing caffe operator documentation
Summary: Add lint rule to check that every time we register a caffe operator to CPU or GPU that documentation is added for the particular operator.

Reviewed By: dzhulgakov

Differential Revision: D5348078

fbshipit-source-id: c3fa22fc7ca8066d5fc8fa780b23d7867fd3380e
2017-07-17 08:17:23 -07:00

88 lines
3.2 KiB
C++

#include "queue_ops.h"
#include <memory>
namespace caffe2 {
CAFFE_KNOWN_TYPE(std::shared_ptr<BlobsQueue>);
REGISTER_CPU_OPERATOR(CreateBlobsQueue, CreateBlobsQueueOp<CPUContext>);
REGISTER_CPU_OPERATOR(EnqueueBlobs, EnqueueBlobsOp<CPUContext>);
REGISTER_CPU_OPERATOR(DequeueBlobs, DequeueBlobsOp<CPUContext>);
REGISTER_CPU_OPERATOR(CloseBlobsQueue, CloseBlobsQueueOp<CPUContext>);
REGISTER_CPU_OPERATOR(SafeEnqueueBlobs, SafeEnqueueBlobsOp<CPUContext>);
REGISTER_CPU_OPERATOR(SafeDequeueBlobs, SafeDequeueBlobsOp<CPUContext>);
REGISTER_CPU_OPERATOR(
WeightedSampleDequeueBlobs,
WeightedSampleDequeueBlobsOp<CPUContext>);
OPERATOR_SCHEMA(CreateBlobsQueue).NumInputs(0).NumOutputs(1);
OPERATOR_SCHEMA(EnqueueBlobs)
.NumInputsOutputs([](int inputs, int outputs) {
return inputs >= 2 && outputs >= 1 && inputs == outputs + 1;
})
.EnforceInplace([](int input, int output) { return input == output + 1; });
OPERATOR_SCHEMA(DequeueBlobs)
.NumInputsOutputs([](int inputs, int outputs) {
return inputs == 1 && outputs >= 1;
})
.SetDoc(R"DOC(
Dequeue the blobs from queue.
)DOC")
.Arg("timeout_secs", "Timeout in secs, default: no timeout")
.Input(0, "queue", "The shared pointer for the BlobsQueue")
.Output(0, "blob", "The blob to store the dequeued data");
OPERATOR_SCHEMA(CloseBlobsQueue).NumInputs(1).NumOutputs(0);
OPERATOR_SCHEMA(SafeEnqueueBlobs)
.NumInputsOutputs([](int inputs, int outputs) {
return inputs >= 2 && outputs >= 2 && inputs == outputs;
})
.EnforceInplace([](int input, int output) { return input == output + 1; })
.SetDoc(R"DOC(
Enqueue the blobs into queue. When the queue is closed and full, the output
status will be set to true which can be used as exit criteria for execution
step.
The 1st input is the queue and the last output is the status. The rest are
data blobs.
)DOC")
.Input(0, "queue", "The shared pointer for the BlobsQueue");
OPERATOR_SCHEMA(SafeDequeueBlobs)
.NumInputsOutputs([](int inputs, int outputs) {
return inputs == 1 && outputs >= 2;
})
.SetDoc(R"DOC(
Dequeue the blobs from queue. When the queue is closed and empty, the output
status will be set to true which can be used as exit criteria for execution
step.
The 1st input is the queue and the last output is the status. The rest are
data blobs.
)DOC")
.Input(0, "queue", "The shared pointer for the BlobsQueue")
.Output(0, "blob", "The blob to store the dequeued data")
.Output(1, "status", "Is set to 0/1 depending on the success of dequeue");
OPERATOR_SCHEMA(WeightedSampleDequeueBlobs)
.NumInputs(1, INT_MAX)
.NumOutputs(2, INT_MAX)
.SetDoc(R"DOC(
Dequeue the blobs from multiple queues. When one of queues is closed and empty,
the output status will be set to true which can be used as exit criteria for
execution step.
The 1st input is the queue and the last output is the status. The rest are
data blobs.
)DOC")
.Input(0, "weights", "Weights for sampling from multiple queues");
NO_GRADIENT(CreateBlobsQueue);
NO_GRADIENT(EnqueueBlobs);
NO_GRADIENT(DequeueBlobs);
NO_GRADIENT(CloseBlobsQueue);
NO_GRADIENT(SafeEnqueueBlobs);
NO_GRADIENT(SafeDequeueBlobs);
NO_GRADIENT(WeightedSampleDequeueBlobs);
}