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Results 1 - 10 of 22 for 1x34x1x3xf32 (0.15 sec)

  1. tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/quantize_composite_functions_weight_only.mlir

        return %1 : tensor<1x3x4x2xf32>
      }
    
      func.func private @composite_conv_fn(%arg0: tensor<1x3x4x3xf32>, %arg1: tensor<2x3x3x2xf32>) -> tensor<1x3x4x2xf32> attributes {_from_xla_call_module} {
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 09 05:56:10 UTC 2024
    - 9.4K bytes
    - Viewed (0)
  2. tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/optimize_graph.mlir

    // CHECK-SAME: %[[ARG_0:.*]]: tensor<1x3x4x3xf32>
    func.func @dont_merge_quantization_followed_by_quantization(%arg0: tensor<1x3x4x3xf32>) -> tensor<1x3x4x3xf32> {
      // CHECK: %[[QUANT_ARG_0:.*]] = stablehlo.uniform_quantize %[[ARG_0]]
      // CHECK: %[[DEQUANT:.*]] = stablehlo.uniform_dequantize %[[QUANT_ARG_0]]
      // CHECK: return %[[DEQUANT]]
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Feb 08 22:40:14 UTC 2024
    - 2.6K bytes
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  3. tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/prepare_quantize/prepare_quantize_per_channel.mlir

        %2 = stablehlo.convolution(%1, %0)
          dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f],
          window = {
            stride = [1, 1], pad = [[0, 0], [1, 1]],
            lhs_dilate = [1, 1],
            rhs_dilate = [1, 1]
          }
          {
            batch_group_count = 1 : i64,
            feature_group_count = 1 : i64
          } : (tensor<1x3x2x3xf32>, tensor<2x3x3x2xf32>)
    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/common/quantization_lib/quantization_driver_test.cc

          %1 = "tf.XlaCallModule"(%0, %cst_0, %cst_1) <{Sout = [#tf_type.shape<1x4x4x3>], module = "", version = 9 : i64}> {_entry_function = @composite_fn_2, _original_entry_function = "composite_fn_2", _tfl_quant_trait = "fully_quantizable"} : (tensor<1x4x4x3xf32>, tensor<3x1x1x3xf32>, tensor<3xf32>) -> tensor<1x4x4x3xf32>
          return %1 : tensor<1x4x4x3xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Apr 25 16:01:03 UTC 2024
    - 7.9K bytes
    - Viewed (0)
  5. tensorflow/compiler/mlir/quantization/tensorflow/tests/cast_bf16_ops_to_f32.mlir

    // RUN: tf-quant-opt %s -quant-cast-bf16-ops-to-f32 | FileCheck %s
    
    func.func @cast_bf16_conv_to_fp32(%arg0: tensor<1x3x4x3xf32>) -> (tensor<1x3x2x2xf32>) {
      %cst = "tf.Const"() {device = "", value = dense_resource<__elided__> : tensor<2x3x3x2xbf16>} : () -> tensor<2x3x3x2xbf16>
      %0 = "tf.Cast"(%arg0) {Truncate = false, device = ""} : (tensor<1x3x4x3xf32>) -> tensor<1x3x4x3xbf16>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 8.4K bytes
    - Viewed (0)
  6. tensorflow/compiler/mlir/quantization/tensorflow/tests/lift_quantizable_spots_as_functions_xla_selective_quantization.mlir

      func.func @conv2d_unmatching_unit(%arg0: tensor<1x3x4x3xf32>) -> (tensor<1x3x2x2xf32>) {
        %cst = "tf.Const"() {device = "", value = dense<1.0> : tensor<2x3x3x2xf32>} : () -> tensor<2x3x3x2xf32>
        %0 = "tf.Cast"(%arg0) {Truncate = false, device = ""} : (tensor<1x3x4x3xf32>) -> tensor<1x3x4x3xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 6.8K bytes
    - Viewed (0)
  7. tensorflow/compiler/mlir/quantization/tensorflow/tests/preprocess_op_weight_only.mlir

        %1 = "tf.BiasAdd"(%0, %cst_0) {data_format = "NHWC", device = ""} : (tensor<*xf32>, tensor<6xf32>) -> tensor<*xf32>
        func.return %1: tensor<*xf32>
      }
      func.func private @composite_depthwise_conv2d_fn(%arg0: tensor<1x3x4x3xf32>, %arg1: tensor<2x3x3x2xf32>) -> tensor<*xf32> attributes {tf_quant.composite_function} {
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 4.7K bytes
    - Viewed (0)
  8. tensorflow/compiler/mlir/quantization/tensorflow/tests/preprocess_op.mlir

        %1 = "tf.BiasAdd"(%0, %cst_0) {data_format = "NHWC", device = ""} : (tensor<*xf32>, tensor<6xf32>) -> tensor<*xf32>
        func.return %1: tensor<*xf32>
      }
      func.func private @composite_depthwise_conv2d_fn(%arg0: tensor<1x3x4x3xf32>, %arg1: tensor<2x3x3x2xf32>) -> tensor<*xf32> attributes {tf_quant.composite_function} {
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 3K bytes
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  9. tensorflow/compiler/mlir/quantization/tensorflow/tests/add_quantization_unit_loc.mlir

    func.func @conv2d_unmatching_loc_pattern(%arg0: tensor<1x3x4x3xf32>) -> (tensor<1x3x2x2xf32>) {
      %cst = "tf.Const"() {device = "", value = dense_resource<__elided__> : tensor<2x3x3x2xbf16>} : () -> tensor<2x3x3x2xbf16>
      %0 = "tf.Cast"(%arg0) {Truncate = false, device = ""} : (tensor<1x3x4x3xf32>) -> tensor<1x3x4x3xbf16>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Tue Oct 03 02:39:10 UTC 2023
    - 3.6K bytes
    - Viewed (0)
  10. tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/convert_func_to_bfloat16.mlir

          stablehlo.return %2 : tensor<f32>
      }) {padding = dense<[[0, 0], [1, 1], [1, 1], [0, 0]]> : tensor<4x2xi64>, window_dimensions = array<i64: 1, 3, 3, 1>} : (tensor<2x3x1x3xf32>, tensor<f32>) -> tensor<2x3x1x3xf32>
      return %1 : tensor<2x3x1x3xf32>
    }
    
    // -----
    
    // CHECK-LABEL: @bitcast_convert_i32_f32(%arg0: tensor<1x256128xi32>) -> tensor<1x256128xbf16>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Feb 08 22:40:14 UTC 2024
    - 6K bytes
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