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Results 1 - 3 of 3 for 1x1x384x384xf32 (0.39 sec)

  1. tensorflow/compiler/mlir/lite/experimental/tac/tests/device-transform-gpu.mlir

    // CHECK:           %[[VAL_10:.*]] = "tfl.concatenation"(%[[VAL_6]], %[[VAL_7]], %[[VAL_8]], %[[VAL_9]]) <{axis = 2 : i32, fused_activation_function = "NONE"}> : (tensor<1x1x384x384xf32>, tensor<1x1x384x384xf32>, tensor<1x1x384x384xf32>, tensor<1x1x384x384xf32>) -> tensor<1x1x1536x384xf32>
    // CHECK:           %[[VAL_11:.*]] = "tfl.reshape"(%[[VAL_10]], %[[VAL_5]]) : (tensor<1x1x1536x384xf32>, tensor<2xi32>) -> tensor<1536x384xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 02 09:41:17 UTC 2024
    - 15.6K bytes
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  2. tensorflow/compiler/mlir/lite/experimental/tac/tests/raise-target-subgraphs.mlir

      %3 = "tfl.pseudo_const"() {value = dense<1.000000e+00> : tensor<1x1x384xf32>} : () -> tensor<1x384x384xf32>
      %4 = "tfl.add"(%2, %3) {tac.device = "GPU", tac.inference_type = "FLOAT", fused_activation_function = "NONE"} : (tensor<1x384x384xf32>, tensor<1x384x384xf32>) -> tensor<1x384x384xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 02 09:41:17 UTC 2024
    - 74.9K bytes
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  3. tensorflow/compiler/mlir/lite/tests/ops.mlir

      // CHECK: "tfl.batch_matmul"(%arg0, %arg1)
      %0 = "tfl.batch_matmul"(%arg0, %arg1) {adj_x = false, adj_y = true} : (tensor<1x4x384x32xf32>, tensor<1x4x384x32x!quant.uniform<i8:f32, 0.11:-16>>) -> tensor<1x4x384x384xf32>
      func.return %0 : tensor<1x4x384x384xf32>
    }
    
    // -----
    
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Jun 06 19:09:08 UTC 2024
    - 189.2K bytes
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