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tensorflow/compiler/mlir/quantization/tensorflow/python/quantize_model.py
related config. representative_dataset: a generator that returns a dictionary in {input_key: input_value} format or a tuple with signature key and a dictionary in {input_key: input_value} format that feeds calibration data for quantizing model. This should be provided when the model is not a QAT model. Returns: A SavedModel object with TF quantization applied. Raises:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 03:36:50 UTC 2024 - 34.2K bytes - Viewed (0) -
tensorflow/compiler/jit/compilability_check_util.h
// constant arguments? Even constant arguments get an _Arg node in the graph // instantiated for Function compilation. The tf2xla kernel for constant _Arg // nodes takes the constant value, converts it to XlaLiteral, and feeds it // to xla::ComputationBuilder.ConstantLiteral, which returns the handle. This // constant XlaLiteral is included in the HLO graph, and subsequently, in // the actual executable, which is copied to the device before being
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Sep 06 19:12:29 UTC 2023 - 14.9K bytes - Viewed (0) -
maven-core/src/main/java/org/apache/maven/execution/MavenSession.java
* Adapt a {@link MavenExecutionRequest} to a {@link Settings} object for use in the Maven core. * We want to make sure that what is ask for in the execution request overrides what is in the settings. * The CLI feeds into an execution request so if a particular value is present in the execution request * then we will take that over the value coming from the user settings. */
Registered: Wed Jun 12 09:55:16 UTC 2024 - Last Modified: Mon Mar 25 10:50:01 UTC 2024 - 16.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/g3doc/tf_dialects.md
// Ops can return multiple outputs and a control token for control // dependencies. // We don’t mention the control token in the return type here, it is implicit. %0, %ctl0 = tf_executor.opA %feed#0, %feed#1 : tensor<*xf32> %1, %ctl1 = tf_executor.opB : tensor<*xf32> %2, %ctl2 = tf_executor.opC %1, %ctl0 : tensor<*xf32> %3, %ctl3 = tf_executor.opD %2 : tensor<*xf32> tf_executor.fetch %3 : tensor<*xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Oct 13 16:33:28 UTC 2021 - 16K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/translate/import_model.cc
// Inserts a placeholder node in the graph to replace a feed output tensor, // and returns the new placeholder node and a boolean indicating if the // original input node was removed from the graph. Uses of the feed output // tensor are replaced with this placeholder node. If the feed output tensor // is of a single output node, the control dependencies are forwarded to the
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 01 11:17:36 UTC 2024 - 183.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_executor_ops.td
(like `tf.Add`) they must be wrapped in the `tf_executor.island` operation. The `tf_executor.graph` operation does not accept any operands, inputs are implicitly captured by the region, representing the feeds to the graph. The region attached to `tf_executor.graph` is terminated by a `tf_executor.fetch` operation. The operands of the terminator correspond to
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 23 19:35:12 UTC 2023 - 22K bytes - Viewed (0) -
tensorflow/cc/saved_model/loader.cc
// leaving behind non-GC'ed state. // // Detailed motivation behind this approach, from ashankar@: // // Each call to Session::Run() that identifies a new subgraph (based on feeds // and fetches) creates some datastructures that live as long as the session // (the partitioned graph, associated executors etc.). // // A pathological case of this would be if say the initialization op
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 02 04:36:00 UTC 2024 - 23K bytes - Viewed (0) -
tensorflow/compiler/jit/compilability_check_util.cc
encapsulating_function, uncompilable_nodes); LogNotCompilable(node, uncompilable_reason); return false; } // _Arg nodes in a top-level function represent feeds and _Retval nodes in a // top-level function represent fetches. if (stack_depth == 1 && (node.type_string() == "_Arg" || node.type_string() == "_Retval")) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 12 06:33:33 UTC 2024 - 30.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/region_control_flow_to_functional.cc
llvm::zip(yield->getOperands().drop_front(1), block.getArguments())) { if (yield_operand != block_arg) return std::nullopt; } } else { // All call results should feed into expected consumer // All results of the call should feed into the yield. if (call.getNumResults() != call_consumer->getNumOperands()) return std::nullopt; }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 28.7K bytes - Viewed (0) -
src/cmd/compile/internal/inline/inlheur/scoring.go
// the in-loop adjustment is 5 (for example), then there is not much // point treating it as inlinable. On the other hand "bar" has a param // property (parameter "x" feeds unmodified to an "if" statement") and // a return property (always returns same constant) meaning that a // given call _could_ be rescored down as much as -35 points-- thus if
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Wed Mar 27 20:42:52 UTC 2024 - 24.2K bytes - Viewed (0)