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Results 1 - 10 of 21 for 16x2x3xf32 (0.2 sec)
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tensorflow/compiler/mlir/lite/tests/prepare-quantize-post-training-16bits.mlir
// CHECK-LABEL: QuantizeUnidirectionalLstmFullPerTensor func.func @QuantizeUnidirectionalLstmFullPerTensor(%arg0: tensor<1x2x3xf32>) -> (tensor<1x2x3xf32>) { %input = "quantfork.stats"(%arg0) {layerStats = dense<[0.0, 1.0]> : tensor<2xf32>} : (tensor<1x2x3xf32>) -> tensor<1x2x3xf32> %1 = "tfl.pseudo_const"() {value = dense<[[0.1]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 26.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/quantize-variables.mlir
%50 = "tfl.read_variable"(%5) : (tensor<!tf_type.resource>) -> tensor<1x2x3xf32> %51 = "quantfork.stats"(%50) {layerStats = dense<[0.0, 1.0]> : tensor<2xf32>} : (tensor<1x2x3xf32>) -> tensor<1x2x3xf32> %52 = "tfl.concatenation"(%51, %0) {axis = 1 : i32, fused_activation_function = "NONE"} : (tensor<1x2x3xf32>, tensor<1x2x3xf32>) -> tensor<1x4x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 20.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/compose-uniform-quantized-type.mlir
%11 = stablehlo.convert %3 : (tensor<1x1x3xi32>) -> tensor<1x1x3xf32> %12 = stablehlo.broadcast_in_dim %11, dims = [0, 1, 2] : (tensor<1x1x3xf32>) -> tensor<1x4x3xf32> // Optional %13 = stablehlo.subtract %10, %12 : tensor<1x4x3xf32> // Precalculated zp_neg. %14 = stablehlo.broadcast_in_dim %4, dims = [0, 1, 2] : (tensor<1x1x3xf32>) -> tensor<1x4x3xf32> // Optional
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 37K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/const-fold.mlir
func.func @div_dense_different_rank() -> tensor<1x2x2xf32> { %cst_0 = arith.constant dense<[[[1.0],[2.0]]]> : tensor<1x2x1xf32> %cst_1 = arith.constant dense<[[2.0, 3.0]]> : tensor<1x2xf32> %0 = "tfl.div"(%cst_0, %cst_1) {fused_activation_function = "NONE"} : (tensor<1x2x1xf32>, tensor<1x2xf32>) -> tensor<1x2x2xf32> func.return %0 : tensor<1x2x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 45.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf-quant.mlir
rhs_quantization_max_val = 127 : i64 } : (tensor<1x6x6x3xf32>, tensor<2x3x3x2x!tf_type.qint8>, tensor<f32>, tensor<i32>) -> tensor<1x4x1x2xf32> func.return %0 : tensor<1x4x1x2xf32> } // ----- // CHECK-LABEL: func @uniform_quantized_convolution_hybrid_same func.func @uniform_quantized_convolution_hybrid_same(%input: tensor<1x2x2x3xf32>) -> tensor<1x2x1x2xf32> {
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/stablehlo/tests/components/tf_to_stablehlo.mlir
}> { _collective_manager_ids = [], device = "" } : (tensor<1x2x2x3xf32>) -> tensor<1x2x2x3xf32> func.return %0: tensor<1x2x2x3xf32> } func.func private @some_func(%arg0: tensor<1x2x2x3xf32>) -> tensor<1x2x2x3xf32> { return %arg0 : tensor<1x2x2x3xf32> } } // CHECK: module // CHECK-NOT: tf.PartitionedCall // CHECK-NOT: some_func
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 08 20:05:12 UTC 2024 - 13.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/insert_calibration_statistics_saver.mlir
%output_0, %min_1, %max_2, %histogram_3 = "tf.CustomAggregator"(%0) <{calibration_method = 1 : i32, id = "1", max_percentile = 0.000000e+00 : f32, min_percentile = 0.000000e+00 : f32, num_bins = 0 : i32}> : (tensor<10x1x3xf32>) -> (tensor<10x1x3xf32>, tensor<f32>, tensor<f32>, tensor<0xi64>) return %output_0 : tensor<10x1x3xf32> } // CHECK-LABEL: @main
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 01:09:50 UTC 2024 - 24.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/ops/stablehlo_op_quant_spec_test.cc
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 04 07:19:09 UTC 2024 - 14.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tpu_sharding_identification.mlir
// Use a four dimension sharding (devices=[1,1,1,1]0) // Since the input tensor only has three dimensions, we expect this to fail. %0 = "tf.XlaSharding"(%arg0) { _XlaSharding = "\08\03\1A\04\01\01\01\01\22\01\00" } : (tensor<1x2x3xi32>) -> tensor<1x2x3xi32> %1 = "tf.A"(%0) : (tensor<1x2x3xi32>) -> (tensor<1x2x3xi32>) func.return %1: tensor<1x2x3xi32> } // ----- // CHECK-LABEL: func @check_retval_sharding_errors
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Feb 20 19:07:52 UTC 2024 - 47.5K 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)