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Shut up "address will always evaluate to 'true'" warnings (#14774)
Summary: Signed-off-by: Edward Z. Yang <ezyang@fb.com> Pull Request resolved: https://github.com/pytorch/pytorch/pull/14774 Differential Revision: D13327969 Pulled By: ezyang fbshipit-source-id: 43380c89eedaaa89467952401b8fd3f5a9ad754a
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@ -21,7 +21,7 @@ class MaxMinOpBase : public Operator<Context> {
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auto* output = Output(0);
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auto* output = Output(0);
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output->ResizeLike(input0);
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output->ResizeLike(input0);
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output->CopyFrom(input0, &context_);
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output->CopyFrom(input0, /* async */ true);
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if (InputSize() == 1) {
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if (InputSize() == 1) {
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return true;
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return true;
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@ -18,7 +18,7 @@ class NegateGradientOp final : public Operator<Context> {
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const auto& in = Input(0);
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const auto& in = Input(0);
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auto* out = Output(0);
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auto* out = Output(0);
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if (out != &in) {
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if (out != &in) {
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out->CopyFrom(in, &context_);
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out->CopyFrom(in, /* async */ true);
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}
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}
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return true;
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return true;
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}
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}
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@ -81,7 +81,7 @@ class ReservoirSamplingOp final : public Operator<Context> {
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if (num_entries == 0) {
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if (num_entries == 0) {
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if (!output_initialized) {
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if (!output_initialized) {
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// Get both shape and meta
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// Get both shape and meta
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output->CopyFrom(input, &context_);
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output->CopyFrom(input, /* async */ true);
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}
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}
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return true;
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return true;
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}
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}
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@ -102,7 +102,7 @@ bool TensorProtosDBInput<Context>::CopyPrefetched() {
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for (int i = 0; i < OutputSize(); ++i) {
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for (int i = 0; i < OutputSize(); ++i) {
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OperatorBase::template Output<Tensor>(i, Context::GetDeviceType())
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OperatorBase::template Output<Tensor>(i, Context::GetDeviceType())
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->CopyFrom(
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->CopyFrom(
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prefetched_blobs_[i].template Get<TensorCPU>(), &this->context_);
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prefetched_blobs_[i].template Get<TensorCPU>(), /* async */ true);
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}
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}
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return true;
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return true;
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}
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}
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@ -51,7 +51,7 @@ class ClipTensorByScalingOp final : public Operator<Context> {
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&context_);
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&context_);
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} else {
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} else {
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if (input_tensor_data != clipped_tensor_data) {
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if (input_tensor_data != clipped_tensor_data) {
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clipped->CopyFrom(input_tensor, &context_);
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clipped->CopyFrom(input_tensor, /*async*/ true);
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}
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}
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}
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}
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