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Results 11 - 13 of 13 for depthwise_conv_2d (0.16 sec)

  1. tensorflow/compiler/mlir/quantization/tensorflow/passes/lift_quantizable_spots_as_functions.cc

        // Disable quantization for the DepthwiseConv since it has no benefits in
        // the XLA opset.
        if (function_name.contains("depthwise_conv2d")) {
          return absl::InternalError(
              "DepthwiseConv2D doesn't get any benefit of quantization in XLA.");
        } else if (function_name.contains("conv2d")) {
          // For Conv2D, the channel dimension must be static to calculate the
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Fri May 10 04:07:09 UTC 2024
    - 16.4K bytes
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  2. tensorflow/compiler/mlir/lite/transforms/prepare_patterns.td

              (TFL_DequantizeOp
                  (TFL_QuantizeOp (TF_ReshapeOp $input, $shape),
                  (UpdateShapeWithAxis<3> $qtype, $old_value))),
      [(UsedBy<"DepthwiseConv2D"> $old_value),
       (CanUpdateShapeWithAxis<3> $qtype, $old_value)],
      [], (addBenefit 10)>;
    
    // The axis is set to 3, because this transpose is from the legalization of
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Tue Apr 30 00:40:15 UTC 2024
    - 10.5K bytes
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  3. tensorflow/compiler/mlir/quantization/tensorflow/passes/preprocess_op.cc

        // than function name.
        if (!function_name.starts_with("composite_")) {
          return failure();
        }
    
        if (function_name.contains("depthwise_conv2d")) {
          // Uniform Quantized op requires weights of tf.DepthwiseConv2dNative to
          // be transformed from [H,W,C,M] to [H,W,1,CxM] where
          // H=height,W=width,C=channel,M=multiplier. Therefore, a reshape op is
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Apr 25 16:01:03 UTC 2024
    - 11.4K bytes
    - Viewed (0)
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