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  1. tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/dynamic_shape.mlir

    // CHECK: func @main(%arg0: tensor<?x19x19x3xf32>) -> tensor<?x9x9x4xf32>
    func.func @main(%arg0: tensor<?x19x19x3xf32>) -> tensor<?x9x9x4xf32> {
      %cst = arith.constant dense<1.0> : tensor<4xf32>
      %cst_3 = arith.constant dense<2.0> : tensor<4x3x3x3xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Mar 24 07:35:24 UTC 2022
    - 716 bytes
    - Viewed (0)
  2. tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_layout_assignment_to_nhwc.mlir

      // CHECK: (%[[ARG0:.*]]: tensor<1x256x150x150xf32>, %[[ARG1:.*]]: tensor<256xf32>)
      // CHECK: %[[CST:.*]] = "tf.Const"() <{value = dense<[0, 2, 3, 1]> : tensor<4xi64>}>
      // CHECK: %[[R0:.*]] = "tf.Transpose"(%[[ARG0]], %[[CST]])
      // CHECK: %[[R1:.*]] = "tf.BiasAdd"(%[[R0]], %[[ARG1]]) <{data_format = "NHWC"}> {device = ""}
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 4.5K bytes
    - Viewed (0)
  3. tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/prepare_quantize/prepare_quantize_per_channel.mlir

    // -----
    
    module {
      // CHECK-LABEL: conv_with_bias_and_relu
      func.func private @conv_with_bias_and_relu(%arg0: tensor<1x3x2x3xf32>) -> tensor<1x2x2x2xf32> {
        %cst = "tf.Const"() {device = "", value = dense<[7.11401462, 7.05456924]> : tensor<2xf32>} : () -> tensor<2xf32>
        // CHECK: %[[q_weight_per_channel:.*]] = "quantfork.qcast"
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Tue Mar 26 07:48:15 UTC 2024
    - 8.6K bytes
    - Viewed (0)
  4. tensorflow/compiler/mlir/quantization/tensorflow/tests/convert_tf_xla_op_to_tf_op.mlir

      func.return %0 : tensor<*xf32>
    }
    
    // CHECK: func @xla_gather
    // CHECK-DAG: %[[cst:.*]] = "tf.Const"() <{value = dense<0> : tensor<2xi64>}> : () -> tensor<2xi64>
    // CHECK-DAG: %[[cst_0:.*]] = "tf.Const"() <{value = dense<1> : tensor<1x1xi64>}> : () -> tensor<1x1xi64>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 3.7K bytes
    - Viewed (0)
  5. tensorflow/compiler/mlir/quantization/tensorflow/tests/prepare_quantize_ptq_per_channel.mlir

        return %8 : tensor<*xf32>
      }
    
    // CHECK-LABEL: conv_with_bias_and_relu
    // CHECK-DAG: %[[cst:.*]] = arith.constant dense<[7.11401462, 7.05456924]> : tensor<2xf32>
    // CHECK-DAG: %[[cst_1:.*]] = arith.constant dense<{{.*}}> : tensor<2x3x3x2xf32>
    
    // CHECK: %[[q0:.*]] = "quantfork.qcast"(%[[cst]]) {volatile}
    // CHECK-SAME: tensor<2x!quant.uniform<i32:f32:0, {0.044169864606680966,0.042867627733627671}>>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Wed Feb 01 10:21:29 UTC 2023
    - 4.2K bytes
    - Viewed (0)
  6. tensorflow/compiler/mlir/lite/tests/unfold-large-splat-constant.mlir

      // CHECK-DAG: %cst = arith.constant dense<0.000000e+00> : tensor<10x10xf32>
      // CHECK-DAG: %cst_0 = arith.constant dense<1000> : tensor<2xi64>
      // CHECK-DAG: %cst_1 = arith.constant dense<1.000000e+00> : tensor<f32>
      // CHECK: %0 = "tfl.fill"(%cst_0, %cst_1) : (tensor<2xi64>, tensor<f32>) -> tensor<1000x1000xf32>
      // CHECK: return %cst, %0 : tensor<10x10xf32>, tensor<1000x1000xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 26 23:53:32 UTC 2022
    - 781 bytes
    - Viewed (0)
  7. tensorflow/compiler/mlir/lite/tests/raise-custom-ops.mlir

      func.return %2 : tensor<4xf32>
    
    // CHECK-NEXT: %[[CST:.*]] = arith.constant dense<1.000000e+00> : tensor<4xf32>
    // CHECK-NEXT: %[[MUL:.*]] = tfl.mul %arg0, %[[CST]] {fused_activation_function = "NONE"} : tensor<4xf32>
    // CHECK-NEXT: %[[CUSTOM_1:.*]] = "tfl.custom_tf"(%[[MUL]], %[[CST]]) ({
    // CHECK-NEXT: ^bb0(%arg1: tensor<4xf32>, %arg2: tensor<4xf32>):
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 4K bytes
    - Viewed (0)
  8. tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model_freeze_assets.mlir

        // CHECK: [[CST:%.+]] = "tf.Const"() <{value = dense<"assets/table.txt"> : tensor<1x!tf_type.string>}> : () -> tensor<1x!tf_type.string>
        // CHECK: [[HASHTABLE:%.+]] = "tf.HashTableV2"()
        // CHECK: "tf.InitializeTableFromTextFileV2"([[HASHTABLE]], [[CST]])
        func.return
      }
    }
    
    // -----
    
    module attributes {tf_saved_model.semantics} {
    
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 4.5K bytes
    - Viewed (0)
  9. tensorflow/compiler/mlir/tensorflow/tests/tpu_tail_with_tobool_op.mlir

        func.return %arg0 : tensor<*xi1>
      }
      func.func @"tpu_subgraph"(%arg0: tensor<*xi64>) -> tensor<*xi1> {
        %cst = "tf.Const"() {value = dense<0> : tensor<i64>} : () -> tensor<i64>
        %cst_0 = "tf.Const"() {value = dense<0> : tensor<i32>} : () -> tensor<i32>
        %cst_1 = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Wed Mar 13 21:23:47 UTC 2024
    - 2.8K bytes
    - Viewed (0)
  10. tensorflow/compiler/mlir/lite/tests/prepare-tf-fake-quant.mlir

      func.return %1, %2 : tensor<2x1xf32>, tensor<2x1xf32>
    
    // CHECK:  %cst = arith.constant
    // CHECK:  %[[FQ:.*]] = "tf.FakeQuantWithMinMaxVars"(%arg0, %arg1, %arg2)
    // CHECK:  %[[T1:.*]] = "tf.Transpose"(%[[FQ]], %cst)
    // CHECK:  %[[T2:.*]] = "tf.Transpose"(%[[FQ]], %cst)
    }
    
    // CHECK-LABEL: fakeQuantFollowedByReshape
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 02 09:41:17 UTC 2024
    - 20.4K bytes
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