fix: Properly cast intermediate Int8 tensors to TensorRT Engines in Fallback #1549
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peri044
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Dec 19, 2022
- Fix compilation error for GPT-2 model arising from Byte-type inputs fed into TensorRT Engine - Update translation dictionary between Torch and TensorRT types to include `at::kByte` - Add field to PartitioningInfo specifying whether to cast Int8 inputs to TensorRT Engines to Int, to avoid error arising from Int8 inputs being fed into non-quantized engines - Add automatic detection of quantized/calibrated models and disable Int8 => Int32 casting in those cases - Fix bug where LoweringInfo target device was not being updated for Python API - Allow `castNode` to force creation of a new node and avoid searching for an existing one to convert - Add test to ensure cast is inserted in the Torch engine preceding a TensorRT engine, when the Byte tensor is an output of the Torch engine
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core/partitioning/shape_analysis.cpp
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| if (partitioning_info.truncate_long_and_double) { | ||
| for (size_t i = 0; i < seg_block.inputs().size(); ++i) { | ||
| if (ivalues_maps[seg_block.raw_inputs()[i]].isTensor()) { | ||
| auto cur_ivalue = ivalues_maps[seg_block.raw_inputs()[i]]; | ||
| at::ScalarType t = cur_ivalue.toTensor().scalar_type(); | ||
| if (t == at::kLong) { | ||
| // we add a cast operation to cast the type to Int64 | ||
| auto cast_node = createCastNode(seg_block, i, true, target_device); | ||
| seg_block.g()->prependNode(cast_node); | ||
| seg_block.inputs()[i]->replaceAllUsesAfterNodeWith(cast_node, cast_node->outputs()[0]); | ||
| } | ||
| } | ||
| } |
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Is this just linter formatting changes?
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I manually made the formatting changes to reduce redundancy of if statements, but they should be functionally equivalent to the previous version
peri044
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Dec 22, 2022
- Address review comments - Improve documentation and logging messages - Restructure casting function to allow for casting of variable data types - Add casting for `at::kByte` segment block inputs as well as segment block outputs
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Description
at::kBytecastNodeto force creation of a new node and avoid searching for an existing one to convertError displayed when passing
Int8inputs to non-quantized TRT Engine:With this PR, GPT-2 now compiles and runs inference successfully.
Fixes #1455
Type of change
Checklist: