27 Commits

Author SHA1 Message Date
Kazuaki Ishizaki
f5813ff8e1 Fix typo in QuantizedType method names
Closes tensorflow/mlir#172

COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/172 from kiszk:quantops e27b57eac8f4c6ef7ee6a6f7b497d3e2f56f6798
PiperOrigin-RevId: 273879164
2019-10-09 20:32:47 -07:00
Christian Sigg
85dcaf19c7 Fix typos, NFC.
PiperOrigin-RevId: 272851237
2019-10-04 04:37:53 -07:00
Feng Liu
8c95223e3c Add axis attribute to the quant.stats op
The first dim length of the axisStats attribute should equals to the slice size
of the input argument when splitted by the axis dimension.

PiperOrigin-RevId: 272798042
2019-10-03 20:29:08 -07:00
Feng Liu
c8961d408e Quantize attribute values by per axis quantization parameters
A new converter with per axis quantization parameters is added to quantize a
dense elements attribute. For each slice along the quantization axis, it
creates an uniform quantized value converter, with different scale and zero
point, and quantizes the values in the slice.

The current implementation doesn't handle sparse elements attributes.

PiperOrigin-RevId: 270121986
2019-09-19 14:12:08 -07:00
River Riddle
f1b100c77b NFC: Finish replacing FunctionPassBase/ModulePassBase with OpPassBase.
These directives were temporary during the generalization of FunctionPass/ModulePass to OpPass.

PiperOrigin-RevId: 268970259
2019-09-13 13:34:27 -07:00
Feng Liu
cf0a782339 Remove the constraint that min / max should stride zero
Since we apply nudging for the zero point to make sure the nudged zerop points
can be in the range of [qmin, qmax], the constraint that rmin / rmax should
stride zero isn't necessary.

This also matches the documentation of tensorflow's FakeQuantWithMinMaxArgs op,
where min and max don't need to stride zero:
https://www.tensorflow.org/api_docs/python/tf/quantization/fake_quant_with_min_max_args

PiperOrigin-RevId: 268296285
2019-09-10 13:26:46 -07:00
Feng Liu
c68d5467d6 Convert ConstFakeQuantPerAxis to qcast and dcast pair
This is also to add the test to the fakeQuantAttrsToType for per-channel fake quant.

PiperOrigin-RevId: 268260032
2019-09-10 10:50:57 -07:00
Feng Liu
d3a6dbc0b8 [NFC] Rename ExpressedToUniformQuantizedType to ExpressedToQuantizedType
PiperOrigin-RevId: 268090906
2019-09-09 15:29:59 -07:00
Feng Liu
27d776fa6d Convert per channel fake quant attributes to type
For per channel fake quant attributes, the returned type should be
UniformQuantizedPerAxisType. Currently, this method isn't under test because we
haven't added the quant_ConstFakeQuantPerAxis op and the convert method.

PiperOrigin-RevId: 268084017
2019-09-09 14:57:59 -07:00
Feng Liu
6de6c2c138 Add tests to verify 0.0 is quantized correctly
We should consider both signed and narrow_range cases.

PiperOrigin-RevId: 266167366
2019-08-29 10:09:22 -07:00
Feng Liu
7dd5efdf2c Fix the equality check of two floating point values
PiperOrigin-RevId: 266022088
2019-08-28 16:39:48 -07:00
River Riddle
ba0fa92524 NFC: Move LLVMIR, SDBM, and StandardOps to the Dialect/ directory.
PiperOrigin-RevId: 264193915
2019-08-19 11:01:25 -07:00
Jacques Pienaar
79f53b0cf1 Change from llvm::make_unique to std::make_unique
Switch to C++14 standard method as llvm::make_unique has been removed (
https://reviews.llvm.org/D66259). Also mark some targets as c++14 to ease next
integrates.

PiperOrigin-RevId: 263953918
2019-08-17 11:06:03 -07:00
Mehdi Amini
926fb685de Express ownership transfer in PassManager API through std::unique_ptr (NFC)
Since raw pointers are always passed around for IR construct without
implying any ownership transfer, it can be error prone to have implicit
ownership transferred the same way.
For example this code can seem harmless:

  Pass *pass = ....
  pm.addPass(pass);
  pm.addPass(pass);
  pm.run(module);

PiperOrigin-RevId: 263053082
2019-08-12 19:13:12 -07:00
River Riddle
300a2bda34 Refactor DenseElementAttr::getValues methods to return full ranges for splats.
The current implementation only returns one element for the splat case, which often comes as a surprise; leading to subtle/confusing bugs. The new behavior will include an iterate over the full range of elements, as defined by the shaped type, by providing the splat value for each iterator index.

PiperOrigin-RevId: 262756780
2019-08-11 18:17:28 -07:00
River Riddle
41968fb475 NFC: Update usages of OwningRewritePatternList to pass by & instead of &&.
This will allow for reusing the same pattern list, which may be costly to continually reconstruct, on multiple invocations.

PiperOrigin-RevId: 262664599
2019-08-09 17:20:29 -07:00
River Riddle
a0df3ebd15 NFC: Implement OwningRewritePatternList as a class instead of a using directive.
This allows for proper forward declaration, as opposed to leaking the internal implementation via a using directive. This also allows for all pattern building to go through 'insert' methods on the OwningRewritePatternList, replacing uses of 'push_back' and 'RewriteListBuilder'.

PiperOrigin-RevId: 261816316
2019-08-05 18:38:22 -07:00
Feng Liu
701266c47a Add an "is_signed" attribute to the quant_ConstFakeQuant op
Some TensorFlow simulated quantize ops such as QuantizeAndDequantizeV2Op have
attribute for the sign of the quantization, so quant_ConstFakeQuant should be
able to represent it with the new attribute is added.

The method for converting these attributes to an QuantizedType is updated to
handle this new argument.

PiperOrigin-RevId: 258810290
2019-07-19 11:39:54 -07:00
Feng Liu
a6d2223584 Support signed and unsigned quantization types
This patch added a new argument to the fakeQuantAttrsToType utility method, so
it can be used to convert min/max to quantized type with different signed
storage types.

PiperOrigin-RevId: 258382538
2019-07-16 13:45:29 -07:00
River Riddle
54cd6a7e97 NFC: Refactor Function to be value typed.
Move the data members out of Function and into a new impl storage class 'FunctionStorage'. This allows for Function to become value typed, which will greatly simplify the transition of Function to FuncOp(given that FuncOp is also value typed).

PiperOrigin-RevId: 255983022
2019-07-01 11:39:00 -07:00
River Riddle
a4c3a6455c Move the emitError/Warning/Remark utility methods out of MLIRContext and into the mlir namespace.
Now that Locations are attributes, they have direct access to the MLIR context. This allows for simplifying error emission by removing unnecessary context lookups.

PiperOrigin-RevId: 255112791
2019-06-25 21:32:23 -07:00
River Riddle
30bbd91056 Simplify usages of SplatElementsAttr now that it inherits from DenseElementsAttr.
PiperOrigin-RevId: 253910543
2019-06-19 23:07:34 -07:00
River Riddle
d8cd96bc8b Refactor DenseElementsAttr to support auto-splatting the dense data on construction. This essentially means that we always auto-detect splat data and only store the minimum amount of data necessary. Support for parsing dense splats, and removing SplatElementsAttr(now that it is redundant) will come in followup cls
PiperOrigin-RevId: 252720561
2019-06-19 22:59:15 -07:00
River Riddle
9e21ab8f52 Add a templated wrapper around RewritePattern that allows for defining match/rewrite methods with an instance of the source op instead of a raw Operation*.
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PiperOrigin-RevId: 250003405
2019-06-01 20:03:22 -07:00
River Riddle
3090a651b7 Update the rewrite methods of each of the DialectConversion patterns to notify the PatternRewriter that the operation is being replaced.
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PiperOrigin-RevId: 248965082
2019-05-20 13:47:44 -07:00
Geoffrey Martin-Noble
090662c5f3 Rename VectorOrTensorType to ShapedType
This is in preparation for making it also support/be a parent class of MemRefType. MemRefs have similar shape/rank/element semantics and it would be useful to be able to use these same utilities for them.

    This CL should not change any semantics and only change variables, types, string literals, and comments. In follow-up CLs I will prepare all callers to handle MemRef types or remove their dependence on ShapedType.

    Discussion/Rationale in https://groups.google.com/a/tensorflow.org/forum/#!topic/mlir/cHLoyfGu8y8

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PiperOrigin-RevId: 248476449
2019-05-20 13:43:58 -07:00
Stella Laurenzo
d4dcf7de9e Move Quantization -> Dialect/QuantOps, FxpMathOps -> Dialect/FxpMathOps.
Adding the additional layer of directory was discussed offline and matches the Target/ tree. The names match the defacto convention we seem to be following where the C++ namespace is ^(.+)Ops/$ matched against the directory name.

    This is in preparation for patching the Quantizer into this tree, which would have been confusing without moving the Quantization dialect to its more proper home. It is left to others to move other dialects if desired.

    Tested:
      ninja check-mlir

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PiperOrigin-RevId: 248171982
2019-05-20 13:41:55 -07:00