- Sort Score
- Result 10 results
- Languages All
Results 1 - 10 of 10 for _einsum (0.22 sec)
-
tensorflow/compiler/mlir/quantization/stablehlo/python/integration_test/quantize_model_test_base.py
] ) def einsum_without_kernel( self, x: core.Tensor, y: core.Tensor ) -> Mapping[str, core.Tensor]: return self._einsum(x, y) def _einsum(self, x, y): out = tensorflow.einsum(equation, x, y) if self._bias is not None: out = nn_ops.bias_add(out, self._bias) return {'output': out} model = EinsumModel()
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 06:31:57 UTC 2024 - 18.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/prepare_lifting.cc
#include "tensorflow/compiler/mlir/quantization/tensorflow/quantization_options.pb.h" #include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h" #include "tensorflow/compiler/mlir/tensorflow/transforms/einsum.h" namespace mlir { namespace quant { namespace { using ::tensorflow::quantization::OpSet; class PrepareLiftingPass : public PassWrapper<PrepareLiftingPass, OperationPass<func::FuncOp>> { public:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 17:58:54 UTC 2024 - 13.3K bytes - Viewed (0) -
requirements_lock_3_12.txt
# via # -r requirements.in # h5py # jax # keras-nightly # ml-dtypes # opt-einsum # scipy # tb-nightly opt-einsum==3.3.0 \ --hash=sha256:2455e59e3947d3c275477df7f5205b30635e266fe6dc300e3d9f9646bfcea147 \ --hash=sha256:59f6475f77bbc37dcf7cd748519c0ec60722e91e63ca114e68821c0c54a46549 # via
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 19:00:33 UTC 2024 - 43.2K bytes - Viewed (0) -
requirements_lock_3_11.txt
# via # -r requirements.in # h5py # jax # keras-nightly # ml-dtypes # opt-einsum # scipy # tb-nightly opt-einsum==3.3.0 \ --hash=sha256:2455e59e3947d3c275477df7f5205b30635e266fe6dc300e3d9f9646bfcea147 \ --hash=sha256:59f6475f77bbc37dcf7cd748519c0ec60722e91e63ca114e68821c0c54a46549 # via
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 19:00:33 UTC 2024 - 42.6K bytes - Viewed (0) -
requirements_lock_3_10.txt
# via # -r requirements.in # h5py # jax # keras-nightly # ml-dtypes # opt-einsum # scipy # tb-nightly opt-einsum==3.3.0 \ --hash=sha256:2455e59e3947d3c275477df7f5205b30635e266fe6dc300e3d9f9646bfcea147 \ --hash=sha256:59f6475f77bbc37dcf7cd748519c0ec60722e91e63ca114e68821c0c54a46549 # via
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 19:00:33 UTC 2024 - 42.6K bytes - Viewed (0) -
requirements_lock_3_9.txt
# via # -r requirements.in # h5py # jax # keras-nightly # ml-dtypes # opt-einsum # scipy # tb-nightly opt-einsum==3.3.0 \ --hash=sha256:2455e59e3947d3c275477df7f5205b30635e266fe6dc300e3d9f9646bfcea147 \ --hash=sha256:59f6475f77bbc37dcf7cd748519c0ec60722e91e63ca114e68821c0c54a46549 # via
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 19:00:33 UTC 2024 - 43K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/BUILD
"decompose_reduce_dataset.cc", "decompose_resource_ops_pass.cc", "device_attribute_to_launch.cc", "device_index_selector.cc", "drop_while_shape_invariant.cc", "einsum.cc", "executor_island_coarsening.cc", "executor_tpuv1_inline_tpu_island.cc", "executor_tpuv1_island_coarsening.cc", "executor_tpuv1_outline_tpu_island.cc",
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 22:19:26 UTC 2024 - 35.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/passes.h
std::unique_ptr<OperationPass<func::FuncOp>> CreateUnrollBatchMatMulPassPass(); // Optional pass which will map TF BatchMatMul to TF Einsum std::unique_ptr<OperationPass<func::FuncOp>> CreateBatchMatMulToEinsumPass(); // Pass that transform Einsum to other TF Ops for the supported variants. std::unique_ptr<OperationPass<func::FuncOp>> CreateTransformEinsumPass(); // Optimizes Tensorflow graph.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 21:18:05 UTC 2024 - 31.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/compose-uniform-quantized-type.mlir
%16 = stablehlo.broadcast_in_dim %6, dims = [0, 1, 2] : (tensor<1x1x1xi32>) -> tensor<8x16x4xi32> %17 = stablehlo.subtract %15, %16 : tensor<8x16x4xi32> // q2 - z2 // Corresponds to einsum expression: b i j, b j d -> b i d %18 = stablehlo.dot_general %14, %17, batching_dims = [0] x [0], contracting_dims = [2] x [1] : (tensor<8x16x16xi32>, tensor<8x16x4xi32>) -> tensor<8x16x4xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 37K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/lift_as_function_call.cc
SmallVector<Value> AppendToVector(const ArrayRef<Value> arguments, Value append) { SmallVector<Value> ret(arguments); ret.push_back(append); return ret; } // Check if the given einsum equation is supported by XlaDotV2. // Conditions: // 1. Two inputs & one output. // 2. No ... in the equation. // 3. Batch dimensions should be the same, or only the left equation should have
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 17:58:54 UTC 2024 - 21.8K bytes - Viewed (0)