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Results 1 - 4 of 4 for 3x4x2xf32 (0.11 sec)

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

            version = 5 : i64
          } : (tensor<?x3x4x3xf32>, tensor<2x3x3x2xf32>, tensor<1x1x1x2xf32>) -> tensor<?x3x4x2xf32>
        %2 = "quantfork.stats"(%1) {layerStats = dense<[5.00000000e-6, 7.00000000e-1]> : tensor<2xf32>} : (tensor<?x3x4x2xf32>) -> tensor<?x3x4x2xf32>
        return %2 : tensor<?x3x4x2xf32>
      }
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 09 05:56:10 UTC 2024
    - 91.6K bytes
    - Viewed (0)
  2. tensorflow/compiler/mlir/tensorflow/tests/unroll-batch-matmul.mlir

      // CHECK: %[[LHS_SPLIT:.*]]:6 = "tf.Split"(%[[SPLITTING_AXIS]], %[[LHS_RESHAPED]]) : (tensor<i32>, tensor<6x4x5xf32>) -> (tensor<1x4x5xf32>, tensor<1x4x5xf32>, tensor<1x4x5xf32>, tensor<1x4x5xf32>, tensor<1x4x5xf32>, tensor<1x4x5xf32>)
      // CHECK: %[[LHS_1:.*]] = "tf.Reshape"(%[[LHS_SPLIT]]#0, %[[MATMUL_LHS_SHAPE]]) : (tensor<1x4x5xf32>, tensor<2xi64>) -> tensor<4x5xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Wed Dec 06 18:42:28 UTC 2023
    - 63.7K bytes
    - Viewed (0)
  3. tensorflow/compiler/mlir/tensorflow/tests/lower_tf.mlir

    // CHECK-SAME: (%[[ARG0:.*]]: tensor<3x4xf32>)
    func.func @expm1(%arg0: tensor<3x4xf32>) -> tensor<3x4xf32> {
      %0 = "tf.Expm1"(%arg0) : (tensor<3x4xf32>) -> tensor<3x4xf32>
      func.return %0 : tensor<3x4xf32>
      // CHECK: %[[ONE:.*]] = "tf.Const"() <{value = dense<1.000000e+00> : tensor<f32>}> : () -> tensor<f32>
      // CHECK: %[[EXP:.*]] = "tf.Exp"(%[[ARG0]]) : (tensor<3x4xf32>) -> tensor<3x4xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Fri Jan 05 18:35:42 UTC 2024
    - 92K bytes
    - Viewed (0)
  4. tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/lift_quantizable_spots_as_functions.mlir

      %0 = stablehlo.constant dense<1> : tensor<3x4x2xi32>
      %1 = stablehlo.constant dense<1> : tensor<2x3x2xi64>
      %2 = "stablehlo.gather"(%0, %1) {
      dimension_numbers = #stablehlo.gather<
        offset_dims = [2, 3],
        collapsed_slice_dims = [0],
        start_index_map = [1, 0],
        index_vector_dim = 2>,
      slice_sizes = array<i64: 1, 2, 2>,
      indices_are_sorted = false
    } : (tensor<3x4x2xi32>, tensor<2x3x2xi64>) -> tensor<2x3x2x2xi32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Fri May 10 04:07:09 UTC 2024
    - 49.8K bytes
    - Viewed (0)
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