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Results 1 - 4 of 4 for write_result (0.25 sec)

  2. github.com/tensorflow/tensorflow

    tensorflow/compiler/jit/build_xla_ops_pass_test.cc 

      TF_ASSERT_OK(MakeXlaCompiledKernel(root.graph(), "cluster_0", "C", &call));
  TF_ASSERT_OK(root.DoShapeInference(call));
  call->AddAttr(kXlaHasReferenceVarsAttr, false);

  Node* write_op = MakeWrite(root, Output(call), "write_result");
  write_op->AddAttr(kXlaHasReferenceVarsAttr, false);

  auto xla_compile = NodeWith(Op("_XlaCompile"), Attr("must_compile", false));
  auto predicated_compilation_key =
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Feb 22 08:47:20 UTC 2024
    - 12.2K bytes
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  3. github.com/gradle/gradle

    subprojects/diagnostics/src/main/java/org/gradle/api/tasks/diagnostics/internal/configurations/renderer/ConsoleConfigurationReportRenderer.java 

                }
        } else {
            writeResults(data, nonLegacyConfigs);
        }
    }

    private void writeResults(ConfigurationReportModel data, List<ReportConfiguration> configs) {
        writeConfigurations(configs);
        if (spec.isIncludeRuleSchema()) {
    Registered: Wed Jun 12 18:38:38 UTC 2024
    - Last Modified: Mon Dec 12 16:17:12 UTC 2022
    - 18.3K bytes
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  4. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/quantization/stablehlo/tests/bridge/convert-tf-quant-types.mlir 

        quantization_axis = -1 : i64, quantization_min_val = -128 : i64, quantization_max_val = 127 : i64
  } : (tensor<2x2xf32>, tensor<f32>, tensor<i32>) -> tensor<2x2x!tf_type.qint8>

  // CHECK: %[[while_result:.*]]:2 = "tf.WhileRegion"(%[[int_0]], %[[int_1]])
  %2:2 = "tf.WhileRegion"(%0, %1) ({
  ^bb0(%carg0: tensor<2x?x!tf_type.qint8>, %carg1: tensor<?x2x!tf_type.qint8>):
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 25.9K bytes
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  5. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/tf2xla/tests/legalize-tf-quant.mlir 

      // %[[RESULT0:.*]] = mhlo.uniform_dequantize %[[WHILE_RESULT]]#0
  %3 = "tf.UniformDequantize"(%2#0, %scales, %zps2) {quantization_axis = -1 : i64, quantization_min_val = -128 : i64, quantization_max_val = 127 : i64} : (tensor<2x?x!tf_type.qint8>, tensor<f32>, tensor<i32>) -> tensor<2x?xf32>

  // %[[RESULT1:.*]] = mhlo.uniform_dequantize %[[WHILE_RESULT]]#0
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 09 01:25:29 UTC 2024
    - 37.3K bytes
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