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Results 1 - 10 of 12 for 256x8x7x16xf32 (0.2 sec)

  1. tensorflow/compiler/mlir/tensorflow/tests/optimize.mlir

      %1 = "tf.BiasAdd"(%0, %bias) {T = "tfdtype$DT_FLOAT", data_format = "NHWC"}: (tensor<256x8x7x16xf32>, tensor<16xf32>) -> tensor<256x8x7x16xf32>
      %2 = "tf.Mul"(%1, %value) {T = "tfdtype$DT_FLOAT"} : (tensor<256x8x7x16xf32>, tensor<16xf32>) -> tensor<256x8x7x16xf32>
      func.return %2 : tensor<256x8x7x16xf32>
    
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Fri Jan 05 18:35:42 UTC 2024
    - 3.3K bytes
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  2. tensorflow/compiler/mlir/lite/quantization/tensorflow/tests/tf_to_quant_4bit.mlir

      %rst = "tf.Conv2D"(%arg, %fq) {T = "tfdtype$DT_FLOAT", data_format = "NHWC", dilations = [1, 2, 3, 1], padding = "SAME", strides = [1, 4, 5, 1]} : (tensor<256x32x32x3xf32>, tensor<3x3x3x16xf32>) -> tensor<256x8x7x16xf32>
      func.return %rst : tensor<256x8x7x16xf32>
    
    // CHECK: %[[CONSTANT0:.*]] = "tf.Const"() <{value = dense<0.000000e+00> : tensor<3x3x3x16xf32>}>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 9.4K bytes
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  3. tensorflow/compiler/mlir/lite/quantization/tensorflow/tests/tf_to_quant.mlir

      %rst = "tf.Conv2D"(%arg, %fq) {T = "tfdtype$DT_FLOAT", data_format = "NHWC", dilations = [1, 2, 3, 1], padding = "SAME", strides = [1, 4, 5, 1]} : (tensor<256x32x32x3xf32>, tensor<3x3x3x16xf32>) -> tensor<256x8x7x16xf32>
      func.return %rst : tensor<256x8x7x16xf32>
    
    // CHECK: %[[CONSTANT0:.*]] = "tf.Const"() <{value = dense<0.000000e+00> : tensor<3x3x3x16xf32>}>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 9.5K bytes
    - Viewed (0)
  4. tensorflow/compiler/mlir/lite/tests/prepare-tf-fake-quant-4bit.mlir

      %rst = "tf.Conv2D"(%arg, %fq) {T = "tfdtype$DT_FLOAT", data_format = "NHWC", dilations = [1, 2, 3, 1], padding = "SAME", strides = [1, 4, 5, 1]} : (tensor<256x32x32x3xf32>, tensor<3x3x3x16xf32>) -> tensor<256x8x7x16xf32>
      func.return %rst : tensor<256x8x7x16xf32>
    
    // CHECK-DAG: %[[CONSTANT:.*]] = arith.constant dense<0.000000e+00> : tensor<16xf32>
    // CHECK-DAG: %[[CONSTANT0:.*]] = arith.constant dense<0.000000e+00> : tensor<16x3x3x3xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 02 09:41:17 UTC 2024
    - 22K bytes
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  5. tensorflow/compiler/mlir/lite/tests/prepare-tf-fake-quant.mlir

      %rst = "tf.Conv2D"(%arg, %fq) {T = "tfdtype$DT_FLOAT", data_format = "NHWC", dilations = [1, 2, 3, 1], padding = "SAME", strides = [1, 4, 5, 1]} : (tensor<256x32x32x3xf32>, tensor<3x3x3x16xf32>) -> tensor<256x8x7x16xf32>
      func.return %rst : tensor<256x8x7x16xf32>
    
    // CHECK-DAG: %[[CONSTANT:.*]] = arith.constant dense<0.000000e+00> : tensor<16xf32>
    // CHECK-DAG: %[[CONSTANT0:.*]] = arith.constant dense<0.000000e+00> : tensor<16x3x3x3xf32>
    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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  6. tensorflow/compiler/mlir/lite/tests/prepare-tf.mlir

    module attributes {tf.versions = {bad_consumers = [], min_consumer = 0 : i32, producer = 268 : i32}} {
    
    func.func @conv(tensor<256x32x32x3xf32>, tensor<3x3x3x16xf32>, tensor<256x3x32x32xf32>) -> (tensor<256x8x7x16xf32>, tensor<256x16x32x32xf32>, tensor<256x8x6x16xf32>, tensor<256x32x32x16xf32>, tensor<256x32x32x16xf32>) {
    ^bb0(%arg0: tensor<256x32x32x3xf32>, %arg1: tensor<3x3x3x16xf32>, %arg2: tensor<256x3x32x32xf32>) :
       // OK
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Wed May 29 07:26:59 UTC 2024
    - 59.8K bytes
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  7. tensorflow/compiler/mlir/lite/tests/optimize.mlir

      %1 = "tfl.add"(%0, %cst) {fused_activation_function = "NONE"} : (tensor<256x8x7x16xf32>, tensor<16xf32>) -> tensor<256x8x7x16xf32>
      %2 = "tfl.add"(%0, %cst_1) {fused_activation_function = "NONE"} : (tensor<256x8x7x16xf32>, tensor<16xf32>) -> tensor<256x8x7x16xf32>
      func.return %1, %2 : tensor<256x8x7x16xf32>, tensor<256x8x7x16xf32>
    
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 16 20:31:41 UTC 2024
    - 284.1K bytes
    - Viewed (0)
  8. tensorflow/compiler/mlir/tf2xla/tests/legalize-tf.mlir

      %0 = "tf.Conv2D"(%arg0, %arg1) {data_format = "NHWC", dilations = [1, 2, 3, 1], padding = "SAME", strides = [1, 4, 5, 1]} : (tensor<256x32x32x6xf32>, tensor<3x3x3x16xf32>) -> tensor<256x8x7x16xf32>
      func.return %0 : tensor<256x8x7x16xf32>
    }
    
    // -----
    
    // CHECK-LABEL: conv3d_simple
    func.func @conv3d_simple(%arg0: tensor<256x32x32x32x6xf32>, %arg1: tensor<3x3x3x3x16xf32>) -> tensor<256x7x6x5x16xf32> {
    
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon May 06 18:46:23 UTC 2024
    - 335.5K bytes
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  9. tensorflow/compiler/mlir/lite/tests/optimize-after-quantization.mlir

      %1 = "tfl.mul"(%0, %cst) {fused_activation_function = "NONE"} : (tensor<256x8x7x3xf32>, tensor<3xf32>) -> tensor<256x8x7x3xf32>
      func.return %1 : tensor<256x8x7x3xf32>
    
      // CHECK: %[[weight:.*]] = arith.constant dense<3.000000e+00> : tensor<3x3x3x3xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Fri Jan 05 18:35:42 UTC 2024
    - 1.4K bytes
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  10. tensorflow/compiler/mlir/lite/tests/prepare-tf-with-allowing-bf16-and-f16-type-legalization.mlir

    func.func @conv_2d_f16(%arg0 : tensor<256x32x32x3xf16>, %arg1 : tensor<3x3x3x16xf16>) -> tensor<256x8x7x16xf16> {
      %0 = "tf.Conv2D"(%arg0, %arg1) {T = "tfdtype$DT_FLOAT", data_format = "NHWC", dilations = [1, 2, 3, 1], padding = "SAME", strides = [1, 4, 5, 1]} : (tensor<256x32x32x3xf16>, tensor<3x3x3x16xf16>) -> tensor<256x8x7x16xf16>
      func.return %0 : tensor<256x8x7x16xf16>
      // CHECK: "tfl.conv_2d"
    }
    
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 26 23:53:32 UTC 2022
    - 2.2K bytes
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