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tensorflow/compiler/mlir/tensorflow/tests/tf_optimize.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 9.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/prepare_quantize/prepare_quantize_per_channel.mlir
-> tensor<1x2x2x2xf32> %3 = "quantfork.stats"(%arg2) {layerStats = dense<[7.05456924, 7.11401462]> : tensor<2xf32>} : (tensor<2xf32>) -> tensor<2xf32> %4 = "quantfork.stats"(%2) {layerStats = dense<[-1.36523, 3.57373]> : tensor<2xf32>} : (tensor<1x2x2x2xf32>) -> tensor<1x2x2x2xf32> %5 = "chlo.broadcast_add"(%4, %3) : (tensor<1x2x2x2xf32>, tensor<2xf32>) -> tensor<1x2x2x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 26 07:48:15 UTC 2024 - 8.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/insert_calibration_statistics_saver_with_skipping.mlir
%output_1, %min_2, %max_3, %histogram_4 = "tf.CustomAggregator"(%0) <{calibration_method = 5 : i32, id = "keeping_id", num_bins = 32 : i32, max_percentile = 0.000000e+00 : f32, min_percentile = 0.000000e+00 : f32}> : (tensor<1x2x2x2xf32>) -> (tensor<1x2x2x2xf32>, tensor<f32>, tensor<f32>, tensor<512xi64>) %1 = "tf.Identity"(%output_1) {device = ""} : (tensor<1x2x2x2xf32>) -> tensor<1x2x2x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 06:31:57 UTC 2024 - 6.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/propagate_quantize_type.mlir
// RUN: tf-quant-opt %s -split-input-file -quant-propagate-quantize-type | FileCheck %s module { func.func @not_propagate_matmul(%arg0: tensor<1x2x2x2xf32>) -> tensor<*xf32> { %cst = "tf.Const"() {value = dense<127> : tensor<2x1024xi8>} : () -> tensor<2x1024xi8> %cst_0 = "tf.Const"() {value = dense<0.0157480314> : tensor<f32>} : () -> tensor<f32> %0 = "tf.Identity"(%cst) : (tensor<2x1024xi8>) -> tensor<2x1024xi8>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 6.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/keras.py
return model class TestModule(tf.Module): def __init__(self): super(TestModule, self).__init__() self.model = mnist_model() # CHECK: func {{@[a-zA-Z_0-9]+}}(%arg0: tensor<1x28x28x1xf32> {tf._user_specified_name = "x", tf_saved_model.index_path = [0]} # CHECK: attributes {{.*}} tf_saved_model.exported_names = ["my_predict"] @tf.function(input_signature=[ tf.TensorSpec([1, 28, 28, 1], tf.float32),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Sep 28 21:37:05 UTC 2021 - 1.7K bytes - Viewed (0)