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Results 41 - 44 of 44 for 2x2xf32 (0.09 sec)

  2. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/lift_quantizable_spots_as_functions_with_quantization_specs.mlir 

    // RUN:   -split-input-file | FileCheck %s --check-prefix=STATIC-RANGE-PTQ-TO-COMPUTE-HEAVY

// STATIC-RANGE-PTQ-TO-COMPUTE-HEAVY: @main
func.func @main(%arg0: tensor<1x2xf32>) -> tensor<1x2xf32> {
  %0 = stablehlo.add %arg0, %arg0 : tensor<1x2xf32>
  return %0 : tensor<1x2xf32>
}
// Tests that `composite_add_fn_1` does not quantize when quantizing
// only compute-heavy ops.
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Tue Apr 02 18:09:38 UTC 2024
    - 8.1K bytes
    - Viewed (0)
  3. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/tf2xla/tests/legalize-tf-include-tf2xla-fallback.mlir 

      func.return %0#0 : tensor<2xi32>
}

// CHECK-LABEL: mirror_pad
func.func @mirror_pad(%arg0: tensor<2x3xcomplex<f64>>) -> tensor<4x7xcomplex<f64>> {
  %0 = mhlo.constant dense<[[1, 1], [2, 2]]> : tensor<2x2xi32>
  // NO_FALLBACK: tf.MirrorPad
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Nov 16 19:04:03 UTC 2023
    - 3.2K bytes
    - Viewed (0)
  4. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/lstm.json 

    // CHECK-DAG: %[[input_18:.*]] = "quantfork.stats"({{.*}}) <{layerStats = dense<[-8.000000e-01, 1.600000e+00]> : tensor<2xf32>}> : (tensor<1x4xf32>) -> tensor<1x4xf32>
// CHECK-DAG: %[[input_19:.*]] = "quantfork.stats"({{.*}}) <{layerStats = dense<[-2.000000e+00, 4.000000e+00]> : tensor<2xf32>}> : (tensor<1x2xf32>) -> tensor<1x2xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Wed May 01 06:25:50 UTC 2024
    - 9.1K bytes
    - Viewed (0)
  5. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/lite/experimental/tac/tests/target-annotation.mlir 

      %2 = "tfl.relu"(%arg0) : (tensor<1xf32>) -> tensor<1xf32>
  // CHECK: tac.device = "CPU", tac.inference_type = "FLOAT"
  %3 = "tfl.pack"(%arg0, %arg1) {axis = 0 : i32, values_count = 2 : i32} : (tensor<1xf32>, tensor<1xf32>) -> tensor<2x1xf32>
  func.return
}

func.func @notAnnotateConst(%arg0: tensor<256x32x32x3xf32>) -> tensor<256x30x30x16xf32> {
  // CHECK-NOT: tac.device tac.inference_type
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Fri May 19 19:32:06 UTC 2023
    - 6.2K bytes
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