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Results 21 - 30 of 50 for PartitionedCall (0.18 sec)

  2. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/tensorflow/tests/guarantee-all-funcs-one-use.mlir 

        func.return
  }
}

// -----
// Test stateful and stateless partitioned calls.
// CHECK-LABEL: func @f
func.func @f() {
  // CHECK: "tf.PartitionedCall"() <{config = "",  config_proto = "", executor_type = "", f = @g}> : () -> ()
  "tf.PartitionedCall"() {config = "",  config_proto = "", executor_type = "", f = @g} : () -> ()
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 2.1K bytes
    - Viewed (0)
  3. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/quantization/tensorflow/tests/replace_cast_hacks_with_tf_xla_ops_large_constants.mlir 

        %cst_5 = "tf.Const"() {value = dense<0> : tensor<512xi32>} : () -> tensor<512xi32>
    %0 = "tf.PartitionedCall"(%arg0, %cst_0, %cst_1) {config = "", config_proto = "", executor_type = "", f = @quantize_i8} : (tensor<1x2240x2240x3xf32>, tensor<f32>, tensor<i32>) -> tensor<1x2240x2240x3xi8>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 5.9K bytes
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  4. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_drq.mlir 

    // -----

module {
  func.func @matmul(%arg0: tensor<1x2x2x3xf32>) -> (tensor<*xf32>) {
    %cst_0 = "tf.Const"() {value = dense<0.000000e+00> : tensor<2x1024xf32>} : () -> tensor<2x1024xf32>
    %1 = "tf.PartitionedCall"(%arg0, %cst_0) {_tfl_quant_trait = "fully_quantizable", config = "", config_proto = "", executor_type = "", f = @composite_matmul_fn} : (tensor<1x2x2x3xf32>, tensor<2x1024xf32>) -> tensor<*xf32>
    func.return %1: tensor<*xf32>
  }
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Wed May 08 19:32:28 UTC 2024
    - 1.6K bytes
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  5. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/quantization/tensorflow/tests/preprocess_op_weight_only.mlir 

        %0 = "tf.PartitionedCall"(%arg0, %cst_1) {_tfl_quant_trait = "fully_quantizable", config = "", config_proto = "", executor_type = "", f = @composite_depthwise_conv2d_fn} : (tensor<1x3x4x3xf32>, tensor<2x3x3x2xf32>) -> tensor<*xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 4.7K bytes
    - Viewed (0)
  6. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/quantization/tensorflow/tests/prepare_quantize.mlir 

          ksize = [1, 2, 2, 1], padding = "VALID", strides = [1, 2, 2, 1]
    } : (tensor<*xf32>) -> tensor<*xf32>
    %3 = "tf.Reshape"(%2, %cst) {device = ""} : (tensor<*xf32>, tensor<2xi32>) -> tensor<*xf32>
    %4 = "tf.PartitionedCall"(%3, %cst_1, %cst_2) {
      _tfl_quant_trait = "fully_quantizable", config = "", config_proto = "",
      executor_type = "", f = @composite_matmul_with_bias_fn_1
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Dec 29 02:42:57 UTC 2022
    - 2.1K bytes
    - Viewed (0)
  7. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/tensorflow/tests/executor_tpuv1_island_inlining/while_op.mlir 

    // RUN: tf-opt %s -tf-executor-tpu-v1-island-inlining | FileCheck %s

// CHECK-NOT: tf.PartitionedCall
// CHECK-NOT: module @_tpu_v1_compat_outlined

module {
  func.func @control_input(%arg0: tensor<i1>) -> tensor<i32> {
    %0:4 = tf_executor.graph {
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Sat Jun 04 03:54:58 UTC 2022
    - 2.8K bytes
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  8. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/quantization/tensorflow/tests/preprocess_op.mlir 

        %0 = "tf.PartitionedCall"(%arg0, %cst_1) {_tfl_quant_trait = "fully_quantizable", config = "", config_proto = "", executor_type = "", f = @composite_depthwise_conv2d_fn} : (tensor<1x3x4x3xf32>, tensor<2x3x3x2xf32>) -> tensor<*xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 3K bytes
    - Viewed (0)
  9. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/quantization/tensorflow/tests/prepare_quantize_ptq.mlir 

        %4 = "quantfork.stats"(%3) {
      layerStats = dense<[-1.0, 0.8]> : tensor<2xf32>
    } : (tensor<*xf32>) -> tensor<*xf32>
    %5 = "tf.PartitionedCall"(%4, %cst_1, %cst_2) {
      _tfl_quant_trait = "fully_quantizable", config = "", config_proto = "",
      executor_type = "", f = @composite_matmul_with_bias_fn_1
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Wed Feb 01 10:21:29 UTC 2023
    - 9.1K bytes
    - Viewed (0)
  10. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/quantization/tensorflow/tests/prepare_quantize_ptq_per_channel.mlir 

        %0 = "quantfork.stats"(%arg0) {layerStats = dense<[1.27501142, 149.824783]> : tensor<2xf32>} : (tensor<1x3x4x3xf32>) -> tensor<1x3x4x3xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Wed Feb 01 10:21:29 UTC 2023
    - 4.2K bytes
    - Viewed (0)
  11. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/quantization/tensorflow/passes/quantized_function_library_xla_weight_only.mlir 

          attributes {tf_quant.quantized_ops = ${quantized_ops}} {

    %accum_out = "tf.PartitionedCall"(%input, %weight) {
        config = "", config_proto = "", executor_type = "", f=@${internal_func_name}
      } : (tensor<*xf32>, tensor<*xi8>) -> tensor<*xf32>

    %out = "tf.PartitionedCall"(%accum_out, %weight_scale) {
        config = "", config_proto = "", executor_type = "", f=@internal_dequantize_f32
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Fri Mar 03 15:43:38 UTC 2023
    - 7K bytes
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