10x1xf32 - Code Search

tensorflow/compiler/mlir/lite/tests/optimize.mlir

  %5 = "tfl.log"(%4) : (tensor<10x1xf32>) -> tensor<10x1xf32>
  %6 = tfl.sub(%2, %5) {fused_activation_function = "NONE"} : (tensor<10x10xf32>, tensor<10x1xf32>) -> tensor<10x10xf32>
  return %6 : tensor<10x10xf32>
 // CHECK: "tfl.log_softmax"(%arg0) : (tensor<10x10xf32>) -> tensor<10x10xf32>
}

// CHECK-LABEL: fuseLogSoftmaxAxisNegativeOne

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/tests/prepare-composite-functions-tf.mlir

// CHECK-DAG:       [[VAL_21:%.*]] = arith.constant...

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/tf2xla/api/v2/testdata/func_with_dead_ops.mlir

tensor<1024xf32>, tensor<32x1024xf32>, tensor<1024x1xf32>, tensor<1024xf32>, tensor<1024x1xf32>, tensor<i64>, tensor<i32>, tensor<32x1024xf32>, tensor<i64>, tensor<i64>, tensor<1024xf32>, tensor<32x1024xf32>, tensor<1024x1xf32>, tensor<1024xf32>, tensor<1024x1xf32>, tensor<i64>, tensor<i32>, tensor<32x1024xf32>, tensor<i64>, tensor<i64>, tensor<1024xf32>, tensor<32x1024xf32>, tensor<1024x1xf32>, tensor<1024xf32>, tensor<1024x1xf32>, tensor<i64>, tensor<i32>, tensor<32x1024xf32>, tensor<i64>, tensor<i64>, tensor<1024xf32>,...

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/stablehlo/tests/compose-uniform-quantized-type.mlir

    %12 = stablehlo.subtract %10, %11 : tensor<1x3xf32>  // q1 * q2 - z1 * q2
    %13 = stablehlo.multiply %12, %4 : tensor<1x3xf32>  // s1 * s2
    %14 = call @uniform_quantize_1(%13, %5, %6) : (tensor<1x3xf32>, tensor<1x1xf32>, tensor<1x1xi8>) -> tensor<1x3xi8>
    %15 = call @uniform_dequantize_0(%14, %5, %6) : (tensor<1x3xi8>, tensor<1x1xf32>, tensor<1x1xi8>) -> tensor<1x3xf32>
    return %15 : tensor<1x3xf32>
  }
// CHECK-NOT: stablehlo.uniform_quantize

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/quantization/stablehlo/passes/bridge/convert_tf_quant_to_mhlo_int_test.cc

  constexpr absl::string_view kProgram = R"mlir(
func.func @main(
    %arg0: tensor<10x10xf32>, %scale: tensor<10xf32>, %zp: tensor<10xi32>
  ) -> tensor<10x10xi8> {
  %0 = "tf.UniformQuantize"(%arg0, %scale, %zp) {
    quantization_axis = 1 : i64,
    quantization_min_val = -128 : i64,
    quantization_max_val = 127 : i64
  } : (tensor<10x10xf32>, tensor<10xf32>, tensor<10xi32>) -> tensor<10x10x!tf_type.qint8>

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/tests/prepare-tf.mlir

  %1 = "tf.MatMul"(%arg0, %arg0) {device = "", transpose_a = false, transpose_b = false} : (tensor<10x10xi32>, tensor<10x10xi32>) -> tensor<10x10xi32>
  %2 = "tf.PreventGradient"(%0) : (tensor<10x10xi32>) -> tensor<10x10xi32>
  %3 = "tf.PreventGradient"(%1) : (tensor<10x10xi32>) -> tensor<10x10xi32>
  %4 = "tf.AddV2"(%2, %3) {device = ""} : (tensor<10x10xi32>, tensor<10x10xi32>) -> tensor<10x10xi32>

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/stablehlo/tests/legalize_hlo.mlir

  %9 = "mhlo.compare"(%0, %8) {comparison_direction = #mhlo<comparison_direction NE>} : (tensor<10x8xf32>, tensor<10x8xf32>) -> tensor<10x8xi1>
  %10 = mhlo.and %7, %9 : tensor<10x8xi1>
  %11 = mhlo.subtract %arg0, %6 : tensor<10x8xf32>
  %12 = mhlo.divide %11, %5 : tensor<10x8xf32>
  %13 = mhlo.add %12, %3 : tensor<10x8xf32>

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/tests/quantize-dynamic-range-float16.mlir

      time_major = false} : (
        tensor<1x2x3xf32>,
        tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>,
        tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>,
        none, none, none,
        tensor<3xf32>, tensor<3xf32>, tensor<3xf32>, tensor<3xf32>,
        none, none,
        tensor<1x3xf32>, tensor<1x3xf32>,
        none, none, none, none) -> tensor<1x2x3xf32>

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/tensorflow/tests/graphdef2mlir/mlir_passthrough_op.pbtxt

# CHECK: mlir_module = "\0Afunc @main(%arg0 : tensor<10xf32>, %arg1 : tensor<10xf32>) -> tensor<10x10xf32> {\0A %add = \22tf.Add\22(%arg0, %arg1) : (tensor<10xf32>, tensor<10xf32>) -> tensor<10xf32>\0A %ret = \22magic.op\22(%add, %add) : (tensor<10xf32>, tensor<10xf32>) -> tensor<10x10xf32>\0A return %ret : tensor<10x10xf32>\0A}\0A"}> {device = ""} : (tensor<10xf32>, tensor<10xf32>) -> tensor<*xf32>

node {
  name: "x"
  op: "Placeholder"
  attr {

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/tests/prepare-quantize-post-training-16bits.mlir

      time_major = false} : (
        tensor<1x2x3xf32>,
        tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>,
        tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>,
        none, none, none,
        tensor<3xf32>, tensor<3xf32>, tensor<3xf32>, tensor<3xf32>,
        none, none,
        tensor<1x3xf32>, tensor<1x3xf32>,
        none, none, none, none) -> tensor<1x2x3xf32>

Registered: Sun Jun 16 05:45:23 UTC 2024

- Last Modified: Thu May 02 09:41:17 UTC 2024

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