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Results 31 - 40 of 60 for 1x3x4x2xf32 (0.3 sec)
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tensorflow/compiler/mlir/quantization/tensorflow/tests/lift_quantizable_spots_as_functions.mlir
func.func @float_conv_strides_equals_to_dilations(%arg0: tensor<1x3x4x3xf32>, %arg1: tensor<2x3x3x2xf32>) -> tensor<*xf32> { %cst = "tf.Const"() {value = dense<0.000000e+00> : tensor<2xf32>} : () -> tensor<2xf32> %0 = "tf.Conv2D"(%arg0, %arg1) {data_format = "NHWC", device = "", dilations = [1, 1, 2, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 2, 1], use_cudnn_on_gpu = true} : (tensor<1x3x4x3xf32>, tensor<2x3x3x2xf32>) -> tensor<*xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 26.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/insert_calibration_statistics_saver_with_skipping.mlir
return %1 : tensor<1x2x2x2xf32> } // CHECK-LABEL: @serving_default // CHECK: %[[CUSTOM_AGGREGATOR_0:.*]], %[[MIN_O:.*]], %[[MAX_O:.*]], %[[HISTOGRAM_0:.*]] = "tf.CustomAggregator"
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/stablehlo/tests/components/pre_calibration_component.mlir
} // CHECK: @main(%[[ARG:.+]]: tensor<1x8x4x4xf32>) -> tensor<1x8x4x4xf32> // Contains the `stablehlo.transpose` op of the arg (e.g. [b, f, 0, 1] to // [b, 0, 1, f]). The weight constant is folded into [0, 1, i, o] format. // CHECK-DAG: %[[CST:.+]] = stablehlo.constant dense<3.000000e+00> : tensor<3x3x8x8xf32> // CHECK: %[[TRANSPOSE_1:.+]] = stablehlo.transpose %arg0, dims = [0, 2, 3, 1] : (tensor<1x8x4x4xf32>) -> tensor<1x4x4x8xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 5.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composite_functions_drq.mlir
%1 = "tf.BiasAdd"(%0, %cst_0) {data_format = "NHWC", device = ""} : (tensor<*xf32>, tensor<3xf32>) -> tensor<*xf32> %2 = "tf.PartitionedCall"(%arg0, %cst_2) {_tfl_quant_trait = "fully_quantizable", config = "", config_proto = "", executor_type = "", f = @composite_depthwise_conv2d_fn_1} : (tensor<1x3x4x3xf32>, tensor<2x3x3x2xf32>) -> tensor<*xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 9.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/lift_quantizable_spots_as_functions_drq.mlir
} // ----- // CHECK-LABEL: lift_float_conv func.func @lift_float_conv(%arg0: tensor<1x3x4x3xf32>) -> (tensor<*xf32>, tensor<*xf32>) { %cst = "tf.Const"() {value = dense<0.000000e+00> : tensor<2xf32>} : () -> tensor<2xf32> %cst_1 = "tf.Const"() {value = dense<3.000000e+00> : tensor<2x3x3x2xf32>} : () -> tensor<2x3x3x2xf32> %0 = "tf.Conv2D"(%arg0, %cst_1) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 11.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/prepare_quantize_ptq.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 01 10:21:29 UTC 2023 - 9.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 16 20:31:41 UTC 2024 - 284.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/fuse_mhlo_convolution.mlir
// CHECK-DAG: %[[CST:.+]] = mhlo.constant dense<[1.000000e-01, 2.000000e-01]> : tensor<2xf32> // CHECK-DAG: %[[CST_BCAST:.+]] = "mhlo.broadcast_in_dim"(%[[CST]]) <{broadcast_dimensions = dense<3> : tensor<1xi64>}> : (tensor<2xf32>) -> tensor<1x1x3x2xf32> // CHECK-DAG: %[[NEW_FILTER:.+]] = mhlo.multiply %[[CST_BCAST]], %[[FILTER]] : tensor<1x1x3x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 4.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/lift_as_function_call_test.cc
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 26.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize.mlir
func.func private @conv(%input: tensor<1x3x4x3xf32> {tf._user_specified_name = "input_tensor"}) -> tensor<*xf32> attributes {tf._construction_context = "kEagerRuntime", tf._input_shapes = [#tf_type.shape<1x3x4x3>]} { %weight = arith.constant dense_resource<__elided__> : tensor<2x3x3x2xf32> %bias = arith.constant dense<[7.11401462, 7.05456924]> : tensor<2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 19:32:28 UTC 2024 - 6.4K bytes - Viewed (0)