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Results 1 - 10 of 34 for 1x1x3x8xf32 (0.13 sec)

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

        %18 = stablehlo.multiply %16, %17 : tensor<1x3x3x4xf32>
        %19 = call @uniform_quantize_1(%18, %5, %6) : (tensor<1x3x3x4xf32>, tensor<1x1x1x1xf32>, tensor<1x1x1x1xi8>) -> tensor<1x3x3x4xi8>
        %20 = call @uniform_dequantize_0(%19, %5, %6) : (tensor<1x3x3x4xi8>, tensor<1x1x1x1xf32>, tensor<1x1x1x1xi8>) -> tensor<1x3x3x4xf32>
        return %20 : tensor<1x3x3x4xf32>
      }
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Tue May 14 17:10:32 UTC 2024
    - 37K bytes
    - Viewed (0)
  2. tensorflow/compiler/mlir/lite/stablehlo/tests/composite-lowering.mlir

    // CHECK: %cst_0 = arith.constant dense<[0, 3, 1, 2]> : tensor<4xi32>
    // CHECK: %2 = "tfl.transpose"(%1, %cst_0) : (tensor<1x1x4x1xf32>, tensor<4xi32>) -> tensor<1x1x1x4xf32>
    // CHECK: return %2 : tensor<1x1x1x4xf32>
    
    
    func.func @avg_pool2d_5(%arg0: tensor<1x1x3x3xf32>) -> (tensor<1x1x2x2xf32>) {
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Jun 06 18:45:51 UTC 2024
    - 32.6K bytes
    - Viewed (0)
  3. tensorflow/compiler/mlir/lite/experimental/tac/tests/e2e/simple-graph.mlir

    // CHECK:  [[VAL_1:%.*]] = "tfl.reshape"(%2, %[[CST]]) {tac.device = "GPU",  tac.inference_type = "FLOAT"} : (tensor<1xf32>, tensor<4xi32>) -> tensor<1x1x1x1xf32>
    // CHECK:  [[VAL_2:%.*]] = "tfl.concatenation"([[VAL_0]], [[VAL_1]]) <{axis = 3 : i32, fused_activation_function = "NONE"}> {tac.device = "GPU", tac.inference_type = "FLOAT"} : (tensor<1x1x1x1xf32>, tensor<1x1x1x1xf32>) -> tensor<1x1x1x2xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 02 09:41:17 UTC 2024
    - 1.6K bytes
    - Viewed (0)
  4. tensorflow/compiler/mlir/lite/quantization/tensorflow/tests/fallback_to_flex_ops_default.mlir

      %1 = "tf.Maximum"(%0, %cst_0) : (tensor<1x3x4x2xf32>, tensor<f32>) -> tensor<1x3x4x2xf32>
      %2 = "tf.Minimum"(%1, %cst_1) : (tensor<1x3x4x2xf32>, tensor<f32>) -> tensor<1x3x4x2xf32>
      func.return %2 : tensor<1x3x4x2xf32>
    // CHECK-DAG: %[[CONST_0:.*]] = "tf.Const"() <{value = dense<{{.*}}> : tensor<1x1x3x2xf32>}> : () -> tensor<1x1x3x2xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 02 09:41:17 UTC 2024
    - 13.4K bytes
    - Viewed (0)
  5. tensorflow/compiler/mlir/quantization/common/lift_as_function_call_test.cc

            func.return %2: tensor<1x3x3x4xf32>
          }
    
          func.func @conv_1_fn(%arg0: tensor<1x3x3x4xf32>) -> tensor<1x3x3x4xf32> {
            %0 = stablehlo.constant dense<2.000000e+00> : tensor<3x3x4x4xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Fri May 10 04:07:09 UTC 2024
    - 26.2K bytes
    - Viewed (0)
  6. tensorflow/compiler/mlir/lite/tests/prepare-quantize-dynamic-range.mlir

      func.return %mm_s : tensor<1x3x3x2xf32>
    
    // CHECK: %[[w:.*]] = arith.constant dense<1.270000e+02> : tensor<512x2xf32>
    // CHECK: %[[q_w:.*]] = "tfl.quantize"(%[[w]]) <{qtype = tensor<512x2x!quant.uniform<i8<-127:127>:f32, 1.000000e+00>>}>
    // CHECK: %[[dq_w:.*]] = "tfl.dequantize"(%[[q_w]]) : (tensor<512x2x!quant.uniform<i8<-127:127>:f32, 1.000000e+00>>) -> tensor<512x2xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 02 09:41:17 UTC 2024
    - 38.2K bytes
    - Viewed (0)
  7. tensorflow/compiler/mlir/lite/experimental/tac/tests/device-transform-gpu.mlir

    // CHECK:           %[[VAL_6:.*]] = "tfl.reshape"(%[[VAL_1]], %[[VAL_2]]) : (tensor<1xf32>, tensor<4xi32>) -> tensor<1x1x1x1xf32>
    // CHECK:           %[[VAL_7:.*]] = "tfl.concatenation"(%[[VAL_5]], %[[VAL_6]]) <{axis = 3 : i32, fused_activation_function = "NONE"}> : (tensor<1x1x1x1xf32>, tensor<1x1x1x1xf32>) -> tensor<1x1x1x2xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 02 09:41:17 UTC 2024
    - 15.6K bytes
    - Viewed (0)
  8. tensorflow/compiler/mlir/lite/tests/optimize.mlir

      %2 = "tfl.select"(%cst_false, %arg0, %arg1) : (tensor<1x2x3x4xi1>, tensor<1x2x3x4xf32>, tensor<1x2x3x4xf32>) -> tensor<1x2x3x4xf32>
      %3 = "tfl.select_v2"(%cst_false, %arg0, %arg1) : (tensor<1x2x3x4xi1>, tensor<1x2x3x4xf32>, tensor<1x2x3x4xf32>) -> tensor<1x2x3x4xf32>
      func.return %0, %1, %2, %3 : tensor<1x2x3x4xf32>, tensor<1x2x3x4xf32>, tensor<1x2x3x4xf32>, tensor<1x2x3x4xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 16 20:31:41 UTC 2024
    - 284.1K bytes
    - Viewed (0)
  9. tensorflow/compiler/mlir/quantization/stablehlo/tests/components/tf_to_stablehlo.mlir

    //   func.return %0#0 : tensor<1x1x2x8xf32>
    // }
    // COM: CHECK: func.func @main() -> tensor<1x1x2x8xf32>
    // COM: CHECK-DAG: %[[CONST:.*]] = stablehlo.constant dense<{{.*}}> : tensor<1x1x2x8xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Apr 08 20:05:12 UTC 2024
    - 13.6K bytes
    - Viewed (0)
  10. tensorflow/compiler/mlir/lite/experimental/tac/tests/get-alternative-subgraph.mlir

    // CHECK:           %[[VAL_8:.*]] = "tfl.reshape"(%[[VAL_7]], %[[VAL_3]]) {tac.device = "GPU", tac.inference_type = "FLOAT"} : (tensor<1x1x1x2xf32>, tensor<1xi32>) -> tensor<2xf32>
    // CHECK:           %[[VAL_9:.*]] = "tfl.reshape"(%[[VAL_8]], %[[VAL_4]]) {tac.device = "GPU", tac.inference_type = "FLOAT"} : (tensor<2xf32>, tensor<2xi32>) -> tensor<2x1xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 02 09:41:17 UTC 2024
    - 20.1K bytes
    - Viewed (0)
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