| Commit message (Collapse) | Author | Age |
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PiperOrigin-RevId: 211487989
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conversions.
That is, instances of sp.ToString() are replaced with string(sp).
This will allow tensorflow::StringPiece::ToString to be removed, which is necessary before it can be replaced with absl::string_view.
PiperOrigin-RevId: 210394878
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PiperOrigin-RevId: 209679086
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PiperOrigin-RevId: 208146417
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PiperOrigin-RevId: 208100633
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Fixed my previous fix.
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PiperOrigin-RevId: 205146924
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inputs
PiperOrigin-RevId: 199776409
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Revert #18413. Too many internal test failures due to the name scope change caused by this change.
Revert #18192. Cannot use re2::StringPiece internally. Need alternative for set call. Will pull and clean this up in a separate change.
PiperOrigin-RevId: 197991247
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scale and offset.
PiperOrigin-RevId: 197812268
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* use nullptr
* converting integer literal to bool, use bool literal instead
* annotate this function with 'override' or (rarely) 'final'
* prefer using 'override' or (rarely) 'final' instead of 'virtual'
PiperOrigin-RevId: 196441181
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conversions.
That is, instances of sp.ToString() are replaced with std::string(sp).
This will allow tensorflow::StringPiece::ToString to be removed, which is necessary before it can be replaced with absl::string_view.
PiperOrigin-RevId: 195162126
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PiperOrigin-RevId: 194997009
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PiperOrigin-RevId: 194031845
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tensorflow::str_util equivalents.
This will allow the deprecated methods to be removed.
PiperOrigin-RevId: 191627087
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sets the maximum size of each created constant.
PiperOrigin-RevId: 191523208
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PiperOrigin-RevId: 190878279
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PiperOrigin-RevId: 189945839
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PiperOrigin-RevId: 189258641
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PiperOrigin-RevId: 189231636
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PiperOrigin-RevId: 188817194
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PiperOrigin-RevId: 188257466
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PiperOrigin-RevId: 186674197
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PiperOrigin-RevId: 186073337
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PiperOrigin-RevId: 185023366
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PiperOrigin-RevId: 184233513
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PiperOrigin-RevId: 184004859
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PiperOrigin-RevId: 183450369
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PiperOrigin-RevId: 183402917
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They don't make sense in the open source repository.
PiperOrigin-RevId: 183140889
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PiperOrigin-RevId: 180301735
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PiperOrigin-RevId: 179953488
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PiperOrigin-RevId: 179306398
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This is a step towards supporting custom Dataset ops built as external
libraries.
PiperOrigin-RevId: 177595688
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PiperOrigin-RevId: 177008504
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PiperOrigin-RevId: 176695926
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PiperOrigin-RevId: 176622438
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PiperOrigin-RevId: 176615107
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PiperOrigin-RevId: 176445215
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PiperOrigin-RevId: 175593063
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renamed it tensorflow::StringPieceHasher. This allows tensorflow::StringPiece to be more easily replaced with absl::string_view (which does not contain a Hasher struct).
PiperOrigin-RevId: 175563786
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PiperOrigin-RevId: 174233361
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1. Tensor names in TF may be in the form of "a:0", "a:1", or "a" as a shorthand
notation of "a:0". FoldConstant library always expected the shorthand notation,
and did not handle the cases where explicit notation was passed to input or
output list. This means that this library could not handle the case when input
or output were not the first output of a node.
2. To match the input nodes in the original graph and the added Recv nodes in
rewritten graph, FoldConstant library used prefix matching. Unfortunately, this
means that when a input name is a prefix of another input name, there is
possibility that wrong Recv node gets matched. For example, if input names were
"placeholder" and "placeholder_1", then it did not handle the case very well.
3. RemoveUnusedNodes() in FoldConstants lib could remove nodes which output
depended on. This happened when an input name points to a node with multiple
outputs and not all outputs of that node were included in the input names.
4. ReplaceSendRecvs() in FoldConstants lib assumed that all input nodes are
removed during rewriting the graph. This assumption is not necessarily true,
and it could add a duplicate node in the graph.
PiperOrigin-RevId: 172641947
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tools/graph_transforms.
By setting this option to false, the transformer will not strip off the shape
information stored as attributes.
PiperOrigin-RevId: 172057283
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PiperOrigin-RevId: 170818644
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graph.
PiperOrigin-RevId: 170309345
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PiperOrigin-RevId: 170001077
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Splits out a shared object (//tensorflow/libtensorflow_framework.so) with core TensorFlow functionality but neither ops nor kernels. This object does include registries for ops, kernels, filesystems, etc. The expectation is that shared objects containing custom ops will have a runtime dependency on this framework shared object: TensorFlow will load the custom op shared object, and the custom op shared object will use the symbols from the framework shared object to register its ops/kernels/etc. rather than (as before this change) relying on those symbols being in the global symbol table.
In this mode, TensorFlow artifacts (_pywrap_tensorflow.so for Python, libtensorflow.so for the C API; currently excluding Android artifacts) will depend on the framework shared object, which will be packaged with the Python pip package and other language distributions. This means that custom ops targeting the framework shared object will work in any language (C++, Java, Go; previously custom ops in these languages required custom Bazel builds).
Adds a config option which reproduces the old behavior (--config=monolithic), which for Python means building a monolithic pywrap_tensorflow shared object and loading its symbols into the global symbol table (with RTLD_GLOBAL). As before, there will be no extra-Bazel custom op support for other languages when compiling in this mode.
Does not change behavior on Windows; the cmake build is still monolithic.
Requires using tf_cc_binary, tf_cc_test, and (rarely) tf_cc_shared_object rules to link in the framework shared object when adding new TensorFlow build rules.
PiperOrigin-RevId: 169572746
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