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Results 1 - 5 of 5 for 2x3x5x4xf32 (0.42 sec)

  2. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/tensorflow/tests/unroll-batch-matmul.mlir 

      // CHECK: return %[[RESULT]] : tensor<2x3x4x6xf32>
}

// -----

func.func @batchMatMulTwoDimAdjXY(%arg0: tensor<2x3x5x4xf32>, %arg1: tensor<2x3x6x5xf32>) -> tensor<2x3x4x6xf32> {
  %0 = "tf.BatchMatMul"(%arg0, %arg1) {adj_x = true, adj_y = true} : (tensor<2x3x5x4xf32>, tensor<2x3x6x5xf32>) -> tensor<2x3x4x6xf32>
  func.return %0 : tensor<2x3x4x6xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Wed Dec 06 18:42:28 UTC 2023
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  3. github.com/tensorflow/tensorflow

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

        %2 = "quantfork.stats"(%1) {layerStats = dense<[4.00000000e-6, 9.80000000e-1]> : tensor<2xf32>} : (tensor<2x3x2x2xf32>) -> tensor<2x3x2x2xf32>
    return %2 : tensor<2x3x2x2xf32>
  }
// Checks that the quantized XlaCallModule has been replaced by a CallOp, which
// calls the quantized entry function.
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 09 05:56:10 UTC 2024
    - 91.6K bytes
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  4. github.com/tensorflow/tensorflow

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

      %4 = stablehlo.broadcast_in_dim %1, dims = [3] : (tensor<4xf32>) -> tensor<1x3x3x4xf32>
  %5 = stablehlo.add %3, %4 : tensor<1x3x3x4xf32>
  %6 = stablehlo.maximum %5, %2 : tensor<1x3x3x4xf32>
  func.return %6: tensor<1x3x3x4xf32>
}
// CHECK: %[[CONST_0:.*]] = stablehlo.constant dense<2.000000e+00>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Fri May 10 04:07:09 UTC 2024
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  5. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/quantization/tensorflow/tests/replace_cast_hacks_with_tf_xla_ops.mlir 

        %6 = "tf.Div"(%arg1, %cst_2) {device = ""} : (tensor<2x3x4x5xf32>, tensor<f32>) -> tensor<2x3x4x5xf32>
    %7 = "tf.AddV2"(%6, %cst_1) {device = ""} : (tensor<2x3x4x5xf32>, tensor<f32>) -> tensor<2x3x4x5xf32>
    %8 = "tf.Maximum"(%7, %cst_1) {device = ""} : (tensor<2x3x4x5xf32>, tensor<f32>) -> tensor<2x3x4x5xf32>
    %9 = "tf.Minimum"(%8, %cst_4) {device = ""} : (tensor<2x3x4x5xf32>, tensor<f32>) -> tensor<2x3x4x5xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 81K bytes
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  6. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/tensorflow/tests/lower_tf.mlir 

      // CHECK: "tf.ConcatV2"(%[[INP0]], %[[INP1]], %[[AXIS]]) : (tensor<1x3x5xf32>, tensor<1x3x5xf32>, tensor<i64>) -> tensor<2x3x5xf32>

  %0 = "tf.Pack"(%arg0, %arg1) : (tensor<3x5xf32>, tensor<3x5xf32>) -> tensor<2x3x5xf32>
  func.return %0 : tensor<2x3x5xf32>
}

// CHECK-LABEL: func @square
func.func @square(%arg0: tensor<3xf32>) -> tensor<3xf32> {
  // CHECK: "tf.Mul"(%arg0, %arg0)
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Fri Jan 05 18:35:42 UTC 2024
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