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Results 1 - 2 of 2 for 2x7x5x4xf32 (0.09 sec)

  2. github.com/tensorflow/tensorflow

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

      %0 = "tfl.slice"(%arg0, %begin0, %shape0) : (tensor<2x3x4x5xf32>, tensor<4xi64>, tensor<4xi64>) -> tensor<2x3x4x4xf32>
  %1 = "tfl.slice"(%arg0, %begin1, %shape1) : (tensor<2x3x4x5xf32>, tensor<4xi64>, tensor<4xi64>) -> tensor<1x2x3x4xf32>
  func.return %0, %1 : tensor<2x3x4x4xf32>, tensor<1x2x3x4xf32>
  // CHECK-DAG: %[[BEGIN_0:.*]] = arith.constant dense<0> : tensor<4xi64>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 16 20:31:41 UTC 2024
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  3. github.com/tensorflow/tensorflow

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

    // CHECK:           })
// CHECK-SAME:        -> tensor<2x3x5x7xf32>
// CHECK:           [[COUNT:%.+]] = mhlo.constant dense<4.000000e+00> : tensor<f32>
// CHECK:           [[DIV_RESULT:%.+]] = chlo.broadcast_divide [[DIVIDEND]], [[COUNT]]
// CHECK-SAME:        broadcast_dimensions = array<i64>
// CHECK-SAME:        -> tensor<2x3x5x7xf32>
// CHECK:           [[CONV16:%.+]] = mhlo.convert [[DIV_RESULT]]
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon May 06 18:46:23 UTC 2024
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