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Results 1 - 10 of 28 for composite_function (0.35 sec)

  1. tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composite_functions_weight_only.mlir

        func.return %1: tensor<*xf32>
      }
      func.func private @composite_matmul_fn_1(%arg0: tensor<2x12xf32>, %arg1: tensor<12x2xf32>) -> tensor<*xf32> attributes {tf_quant.composite_function} {
        %0 = "tf.MatMul"(%arg0, %arg1) {attr_map = "0:transpose_a,1:transpose_b", device = "", transpose_a = false, transpose_b = false} : (tensor<2x12xf32>, tensor<12x2xf32>) -> tensor<*xf32>
        return %0 : tensor<*xf32>
      }
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 11.3K bytes
    - Viewed (0)
  2. tensorflow/compiler/mlir/quantization/tensorflow/tests/prepare_quantize_drq_per_channel.mlir

        func.return %1: tensor<*xf32>
      }
      func.func private @composite_matmul_fn(%arg0: tensor<1x2x2x3xf32>, %arg1: tensor<2x1024xf32>) -> tensor<*xf32> attributes {tf_quant.composite_function} {
        %0 = "tf.MatMul"(%arg0, %arg1) {attr_map = "0:transpose_a,1:transpose_a", device = "", transpose_a = false, transpose_b = false} : (tensor<1x2x2x3xf32>, tensor<2x1024xf32>) -> tensor<*xf32>
        return %0 : tensor<*xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 6.8K bytes
    - Viewed (0)
  3. tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/insert_calibration_statistics_saver.mlir

    // -----
    
    // No CustomAggregator ops exist.
    func.func private @composite_conv2d_with_bias_and_relu6_fn_1(%arg0: tensor<1x3x4x3xf32>, %arg1: tensor<2x3x3x2xf32>, %arg2: tensor<2xf32>) -> tensor<1x2x2x2xf32> attributes {tf_quant.composite_function} {
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Apr 25 01:09:50 UTC 2024
    - 24.3K bytes
    - Viewed (0)
  4. tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composite_functions_drq.mlir

        func.return %1: tensor<*xf32>
      }
      func.func private @composite_matmul_fn_1(%arg0: tensor<2x12xf32>, %arg1: tensor<12x2xf32>) -> tensor<*xf32> attributes {tf_quant.composite_function} {
        %0 = "tf.MatMul"(%arg0, %arg1) {attr_map = "0:transpose_a,1:transpose_b", device = "", transpose_a = false, transpose_b = false} : (tensor<2x12xf32>, tensor<12x2xf32>) -> tensor<*xf32>
        return %0 : tensor<*xf32>
      }
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Fri Jan 05 18:35:42 UTC 2024
    - 9.8K bytes
    - Viewed (0)
  5. tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composite_functions_xla.mlir

        func.return %6 : tensor<*xf32>
      }
      func.func private @composite_conv2d_with_bias_and_relu6_fn_1(%arg0: tensor<*xf32>, %arg1: tensor<*xf32>, %arg2: tensor<2xf32>) -> tensor<*xf32> attributes {tf_quant.composite_function} {
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Jan 08 01:16:10 UTC 2024
    - 25.2K bytes
    - Viewed (0)
  6. tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/lift_quantizable_spots_as_functions_with_quantization_specs.mlir

    // DISABLE-ALL-DOT-GENERAL: return %[[XLA_CALL_MODULE:.+]] : tensor<1x1x64xf32>
    // DISABLE-ALL-DOT-GENERAL: }
    
    // DISABLE-ALL-DOT-GENERAL-LABEL: private @composite_dot_general_fn_1
    // DISABLE-ALL-DOT-GENERAL-SAME: tf_quant.composite_function
    // DISABLE-ALL-DOT-GENERAL: %[[DOT_GENERAL:.+]] = stablehlo.dot_general %arg0, %arg1
    // DISABLE-ALL-DOT-GENERAL: return %[[DOT_GENERAL:.+]] : tensor<1x1x64xf32>
    // DISABLE-ALL-DOT-GENERAL: }
    
    // -----
    
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Tue Apr 02 18:09:38 UTC 2024
    - 8.1K bytes
    - Viewed (0)
  7. tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/replace_stablehlo_ops_in_main_function_with_xla_call_module_ops.mlir

      // CHECK: }
    
      // CHECK: @composite_dot_general_fn_1
      // CHECK-NOT: tf_quant.composite_function
      func.func private @composite_dot_general_fn_1(%arg0: tensor<1x1024xf32>, %arg1: tensor<1024x3xf32>, %arg2: tensor<1x3xf32>) -> tensor<1x3xf32> attributes {_from_xla_call_module, tf_quant.composite_function} {
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Apr 25 01:09:50 UTC 2024
    - 39.8K bytes
    - Viewed (0)
  8. tensorflow/compiler/mlir/quantization/tensorflow/tests/prepare_quantize_drq.mlir

        func.return %1: tensor<*xf32>
      }
      func.func private @composite_matmul_fn(%arg0: tensor<1x2x2x3xf32>, %arg1: tensor<2x1024xf32>) -> tensor<*xf32> attributes {tf_quant.composite_function} {
        %0 = "tf.MatMul"(%arg0, %arg1) {attr_map = "0:transpose_a,1:transpose_a", device = "", transpose_a = false, transpose_b = false} : (tensor<1x2x2x3xf32>, tensor<2x1024xf32>) -> tensor<*xf32>
        return %0 : tensor<*xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 6.7K bytes
    - Viewed (0)
  9. tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composit_functions_debugging.mlir

        %0 = "tf.MatMul"(%arg0, %arg1) {attr_map = "0:transpose_a,1:transpose_b", device = "", transpose_a = false, transpose_b = false} : (tensor<2x2xf32>, tensor<2x2xf32>) -> tensor<2x2xf32>
        return %0 : tensor<2x2xf32>
      }
      func.func private @composite_matmul_fn_2_0(%arg0: tensor<2x2xf32>, %arg1: tensor<2x2xf32>) -> tensor<2x2xf32> attributes {tf_quant.composite_function} {
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Nov 06 01:23:21 UTC 2023
    - 80.5K bytes
    - Viewed (0)
  10. tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composite_functions.mlir

        func.return %6, %7 : tensor<*xf32>, tensor<*xf32>
      }
      func.func private @composite_conv2d_with_bias_and_relu6_fn_2(%arg0: tensor<*xf32>, %arg1: tensor<*xf32>, %arg2: tensor<2xf32>) -> tensor<*xf32> attributes {tf_quant.composite_function} {
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Nov 06 01:23:21 UTC 2023
    - 15.2K bytes
    - Viewed (0)
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