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Results 1 - 6 of 6 for HWIO (0.04 sec)

  1. tensorflow/compiler/mlir/quantization/common/attrs_and_constraints.h

    inline constexpr std::array<int64_t, 4> kNchwToNhwcPermutation = {0, 2, 3, 1};
    
    // Permutation from the OIHW (== (output features, input features, height,
    // width)) tensor format to HWIO. This is commonly used to transpose convolution
    // weights represented as OIHW format to HWIO, which is more desirable for
    // certain downstream optimization passes (e.g. XLA).
    inline constexpr std::array<int64_t, 4> kOihwToHwioPermutation = {2, 3, 1, 0};
    
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Apr 25 16:01:03 UTC 2024
    - 9.9K bytes
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  2. tensorflow/compiler/mlir/lite/stablehlo/transforms/fuse_convolution_pass.cc

                    "non-broadcastable operands";
          });
        }
        filter_value = filter.getValue();
        mul_value = multiplier.getValue();
        // In MHLO, Conv filter is in HWIO format, Depthwise conv filter is in HW1O
        // format and backprop input conv filter is in HWOI format.
        // Only fuses multiplier if all dimensions other than the out channel
        // dimension are equal to 1.
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Feb 22 22:21:19 UTC 2024
    - 8.3K bytes
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  3. tensorflow/compiler/mlir/lite/transforms/prepare_tf.cc

      // format HWIO to TFLite Conv2D op filter data format OHWI and return Value
      // for the converted filter.  Requires that filter is verified by the match
      // method that it is a 4-D RankedTensorType.
      Value legalizeFilter(PatternRewriter &rewriter, Location loc,
                           Value filter) const {
        // Create a constant op for HWIO to OHWI transpose permutation.
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Tue May 28 21:49:50 UTC 2024
    - 64.6K bytes
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  4. tensorflow/compiler/mlir/tf2xla/tests/legalize-tf-prefer-tf2xla.mlir

      %conv2d = "tf._FusedConv2D"(%input, %filter, %bias, %act, %input_scale, %side_input_scale) {
        data_format = "NHWC", dilations = [1, 1, 1, 1], epsilon = 9.99999974E-5 : f32, explicit_paddings = [], filter_format = "HWIO", fused_ops = ["BiasAdd", "Relu"], leakyrelu_alpha = 2.000000e-01 : f32, num_args = 2 : i64, operandSegmentSizes = array<i32: 1, 1, 2, 2>, padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Sat Apr 06 15:32:52 UTC 2024
    - 15.8K bytes
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  5. tensorflow/compiler/mlir/tf2xla/transforms/legalize_tf.cc

      int64_t num_dims = num_spatial_dims + 2;
    
      int64_t batch_dim = GetTensorBatchDimIndex(num_dims, format);
      int64_t feature_dim = GetTensorFeatureDimIndex(num_dims, format);
    
      // Filters data_format is always HWIO so input channels dimension is after
      // all spatial dimensions.
      int64_t kernel_input_feature_dim = num_spatial_dims;
      int64_t kernel_output_feature_dim = num_spatial_dims + 1;
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Tue Jun 11 20:00:43 UTC 2024
    - 291.8K bytes
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  6. tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td

        DefaultValuedOptionalAttr<TF_AnyStrAttrOf<["NHWC", "NCHW", "NCHW_VECT_C"]>, "\"NHWC\"">:$data_format,
        DefaultValuedOptionalAttr<TF_AnyStrAttrOf<["HWIO", "OIHW", "OIHW_VECT_I"]>, "\"HWIO\"">:$filter_format,
        DefaultValuedOptionalAttr<I64ArrayAttr, "{1, 1, 1, 1}">:$dilations,
        DefaultValuedOptionalAttr<BoolAttr, "true">:$use_cudnn_on_gpu,
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Tue Jun 11 23:24:08 UTC 2024
    - 793K bytes
    - Viewed (0)
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