pytorch/caffe2/utils/cast_test.cc
Sebastian Meßmer 49f8581745
Update from facebook (#7855)
* [mpscnn] MPSCNNChannelShuffle

att

* [Easy] Adding tags as an argument to the functional layer

Without it "tags" would be added as an argument to the operator.

The change here is based on the assumption that there is no operator that takes "tags" as an argument.

* Fix locally_connected_op schema check.

Fix locally_connected_op schema check.

* [C2] Add TypeAndShape inference for few more operators

As desc

* [c2] Shape inference should support 0 as dimension

Tensors can have 0 in their dimension.

* Make MockHiveReader loop over and support max_examples

Replace DatasetReader with RandomDatasetReader.

So that Mock Hive Reader can simulate a large data input using a small sample file as source.

* Utility function to wipe cache between benchmark runs

Caffe2 benchmark does not wipe out cache between runs, and this potentially creates an unrealistically optimistic picture of performance. This diff adds utility function to wipe out the cache.

* Allow caffe2 GlobalInit to be invoked multiple times

Allow caffe2 GlobalInit to be invoked multiple times. Will re-parse gflags and update logging levels on successive invocations, but will not re-run init functions or perform other one-time initialization.

* Add Caffe2 GlobalInitIsCalledGuard to base net and operator classes

Warn if caffe2's GlobalInit function has not been invoked before creating an operator or net object. This is based on discussion here: https://fb.quip.com/kqGIAbmK7vNG

* Rethrow current exception on failure

Rethrow current exception instead of copy constructing a new one on op failure.

* Make `clone()` return subclass of List/Struct

`clone()` is not working correctly when we subclass those classes

* Wipe the cache before the net run

the util function is copied from D7409424
will rebase once D7409424 is landed.

* [Caffe2] [Mobile] Support utils/cast.h::GetCastDataType with LITE_PROTO builds

* Correct includes

async_polling include -> async_base include

* Prepare execution flags for executor migration

Making async_scheduling aware of underlying net type to prepare for executor
migration

* Add operator level observers into async executor

Adding operator level observers into RunAsync operators' calls

* Cleanup TEST_Benchmark

Remove duplicate code and provide default implementation in NetBase

* [C2] Fix type and shape inference for binary comparison ops

As desc.

* Add GlobalInit to predictor to ensure initialization is always done before prediction

FACEBOOK:

Redo D7651453 the correct way.

Now use a static variable for the arguments passed to GLog

* Remove spammy log message

This method is currently used in various places inside Caffe itself.

* Disable events for operators inside a chain

We don't need to use events in operators within a chain because the chain is
always scheduled on a single stream, keeping only first and last event for
scheduling purposes

* Ensure correct finish run order

In rare cases we might call finishRun and trigger net's destruction while
another worker is still holding shared_ptr to a thread pool, that can cause
thread pool destruction from within a worker thread in case no other nets are
using the pool. This diff fixes the order of calling finishRun and also changes
pool() to return raw pointer to keep pool's ownership within the net

* Reduce unnecessary polling

Make sure we don't waste CPU by polling operators that we can set an efficient
callbacks on

* Squash commit of syncing 9506eeb from github to fbcode

Patch xplat buck fix

add virtual destructor to OptimizationPass

add virtual destructor to OptimizationPass

build fixes for sync

build fixes for sync

* Fix net tracing

Fix net tracing from async_scheduling

* Fix logging
2018-05-29 11:38:02 -07:00

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C++

#include <memory>
#include <vector>
#include <gtest/gtest.h>
#include "caffe2/utils/cast.h"
namespace caffe2 {
TEST(CastTest, GetCastDataType) {
auto castOp = [](std::string t) {
// Ensure lowercase.
std::transform(t.begin(), t.end(), t.begin(), ::tolower);
auto op = CreateOperatorDef("Cast", "", {}, {});
AddArgument("to", t, &op);
return op;
};
#define X(t) \
EXPECT_EQ( \
TensorProto_DataType_##t, \
cast::GetCastDataType(ArgumentHelper(castOp(#t)), "to"));
X(FLOAT);
X(INT32);
X(BYTE);
X(STRING);
X(BOOL);
X(UINT8);
X(INT8);
X(UINT16);
X(INT16);
X(INT64);
X(FLOAT16);
X(DOUBLE);
#undef X
}
} // namespace caffe2