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Results 111 - 120 of 303 for 1xf32 (0.03 sec)
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tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/lstm.mlir
"TANH", input_to_cell_intermediate = tensor<0xf32>, input_to_forget_intermediate = tensor<0xf32>, input_to_input_intermediate = tensor<0xf32>, input_to_output_intermediate = tensor<0xf32>, proj_clip = 0.000000e+00 : f32, time_major = false} : (tensor<?x?x?xf32>, tensor<?x?xf32>, tensor<?x?xf32>, tensor<?x?xf32>, tensor<?x?xf32>, tensor<?x?xf32>, tensor<?x?xf32>, tensor<?x?xf32>, tensor<?x?xf32>, tensor<?xf32>, tensor<?xf32>, tensor<?xf32>, tensor<?xf32>, tensor<?xf32>, tensor<?xf32>, tensor<?xf32>,...
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 20.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/strip_tf_attributes.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Oct 25 20:04:10 UTC 2022 - 1.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf-quant.mlir
} : (tensor<2x!tf_type.qint8>, tensor<f32>, tensor<i32>) -> tensor<2xf32> func.return %1 : tensor<2xf32> } // ----- // CHECK-LABEL: func @uniform_quantize_and_dequantize_per_axis func.func @uniform_quantize_and_dequantize_per_axis(%arg0 : tensor<2x2xf32>) -> tensor<2x2xf32> { %scales = "tf.Const"() { value = dense<[1.0, 2.0]> : tensor<2xf32> } : () -> tensor<2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 01:25:29 UTC 2024 - 37.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/lift_quantizable_spots_as_functions.mlir
%4 = "tf.BiasAdd"(%3, %cst) {data_format = "NHWC", device = ""} : (tensor<*xf32>, tensor<2xf32>) -> tensor<*xf32> %5 = "tf.Relu6"(%4) {device = ""} : (tensor<*xf32>) -> tensor<*xf32> func.return %2, %5 : tensor<*xf32>, tensor<*xf32> } func.func @float_conv_1(%arg0: tensor<1x3x4x3xf32>, %arg1: tensor<2x3x3x2xf32>) -> (tensor<*xf32>, 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/tensorflow/tests/optimize.mlir
%2 = "tf.Mul"(%1, %value) {T = "tfdtype$DT_FLOAT"} : (tensor<256x8x7x16xf32>, tensor<16xf32>) -> tensor<256x8x7x16xf32> func.return %2 : tensor<256x8x7x16xf32> // CHECK-DAG: %[[cst:.*]] = "tf.Const{{.*}} dense<8.000000e+00> : tensor<3x3x3x16xf32> // CHECK-DAG: %[[cst_0:.*]] = "tf.Const{{.*}} dense<1.200000e+01> : tensor<16xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 3.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/composite-lowering.mlir
%12 = mhlo.clamp %9, %11, %1 : tensor<2xf32> %13 = mhlo.multiply %arg0, %12 : tensor<2xf32> %14 = mhlo.divide %13, %1 : tensor<2xf32> return %14 : tensor<2xf32> } // CHECK-LABEL: func.func @hardswish( // CHECK-SAME: %[[VAL_0:.*]]: tensor<2xf32>) -> tensor<*xf32> { // CHECK: %[[VAL_1:.*]] = "tfl.hard_swish"(%[[VAL_0]]) : (tensor<2xf32>) -> tensor<2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 18:45:51 UTC 2024 - 32.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/unidirectional_sequence_lstm.mlir
func.func @main(tensor<4x4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4x4xf32>, tensor<4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>) -> tensor<4x4x4xf32> { // CHECK: { // CHECK-NEXT: version: 3, // CHECK-NEXT: operator_codes: [ {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Dec 06 18:55:51 UTC 2023 - 11.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/tensorflow/tests/tf_to_quant_4bit.mlir
%min = arith.constant dense<0.0> : tensor<16xf32> %max = arith.constant dense<15.0> : tensor<16xf32> %mini = "tf.Identity"(%min) : (tensor<16xf32>) -> tensor<16xf32> %maxi = "tf.Identity"(%max) : (tensor<16xf32>) -> tensor<16xf32> %fq = "tf.FakeQuantWithMinMaxVarsPerChannel"(%in, %mini, %maxi) {num_bits = 3, narrow_range = false} : (tensor<3x3x3x16xf32>, tensor<16xf32>, tensor<16xf32>) -> tensor<3x3x3x16xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 9.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize-dynamic-range.mlir
// MinElement-LABEL: QuantizeCustomOp func.func @QuantizeCustomOp(%arg0: tensor<1x1x1x1xf32>) -> (tensor<*xf32>, tensor<*xf32>, tensor<*xf32>) attributes {tf.entry_function = {inputs = "input", outputs = "custom_op"}} { %0 = "quantfork.stats"(%arg0) {layerStats = dense<[0.000000e+00, 2.550000e+02]> : tensor<2xf32>} : (tensor<1x1x1x1xf32>) -> tensor<1x1x1x1xf32> %w_1 = arith.constant dense<127.0> : tensor<4096x1x1x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 38.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/quantize-dynamic-range-float16.mlir
none, none, none, tensor<3xf32>, tensor<3xf32>, tensor<3xf32>, tensor<3xf32>, none, none, tensor<1x3xf32>, tensor<1x3xf32>, none, none, none, none) -> tensor<1x2x3xf32> %17 = "quantfork.stats"(%16) {layerStats = dense<[-0.1, 0.1]> : tensor<2xf32>} : (tensor<1x2x3xf32>) -> tensor<1x2x3xf32> func.return %17 : tensor<1x2x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 4.6K bytes - Viewed (0)