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Results 11 - 20 of 30 for 4x5xf32 (0.26 sec)
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tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/lstm.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Dec 06 18:55:51 UTC 2023 - 10.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/lstm_asym_attr.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Dec 06 18:55:51 UTC 2023 - 10.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/insert_calibration_statistics_saver.mlir
return %3 : tensor<1x3xf32> } func.func private @composite_matmul_with_bias_fn_2(%arg0: tensor<1x4xf32>, %arg1: tensor<4x3xf32>, %arg2: tensor<3xf32>) -> tensor<1x3xf32> attributes {tf_quant.composite_function} { %0 = "tf.MatMul"(%arg0, %arg1) <{grad_a = false, grad_b = false, transpose_a = false, transpose_b = false}> {attr_map = "0:transpose_a,1:transpose_b", device = ""} : (tensor<1x4xf32>, tensor<4x3xf32>) -> tensor<1x3xf32>
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/lite/tests/flatbuffer2mlir/lstm.mlir
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/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,
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/tensorflow/tests/executor_tpuv1_island_coarsening/executor_tpuv1_island_coarsening.mlir
%add_out, %add_control = tf_executor.island wraps "tf.AddV2"(%const_out, %const_out) {_xla_compile_device_type = "TPU", _replication_info = "cluster"} : (tensor<4x4xf32>, tensor<4x4xf32>) -> tensor<4x4xf32> %replicated_out, %replicated_control = tf_executor.island wraps "tf.TPUReplicatedOutput"(%add_out) : (tensor<4x4xf32>) -> (tensor<4x4xf32>)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Aug 02 03:15:59 UTC 2022 - 36.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/replace_stablehlo_ops_in_main_function_with_xla_call_module_ops.mlir
_collective_manager_ids = [], device = "" } : (tensor<3x3xf32>, tensor<3x3xf32>) -> tensor<3x3xf32> %3 = "tf.PartitionedCall"(%2, %1) <{ config = "", config_proto = "", executor_type = "", f = @some_other_func }> { _collective_manager_ids = [], device = "" } : (tensor<3x3xf32>, tensor<3x3xf32>) -> tensor<3x3xf32> return %3 : tensor<3x3xf32> } // CHECK: func.func @main
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 01:09:50 UTC 2024 - 39.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-tf-fake-quant.mlir
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/lite/tests/prepare-tf-fake-quant-4bit.mlir
func.func @fakeQuantPerChannelForActivation(%arg0: tensor<8x4xf32>) -> (tensor<8x4xf32>) { %arg1 = arith.constant dense<[0.0, -1.0, 1.0, 0.0]> : tensor<4xf32> %arg2 = arith.constant dense<[15.0, 14.0, 16.0, 1.0e-9]> : tensor<4xf32> %0 = "tf.FakeQuantWithMinMaxVarsPerChannel"(%arg0, %arg1, %arg2) {num_bits = 3, narrow_range = false} : (tensor<8x4xf32>, tensor<4xf32>, tensor<4xf32>) -> tensor<8x4xf32> func.return %0 : tensor<8x4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 22K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/defer_activation_transpose.mlir
func.func @add_with_activation_transpose_rank_two(%arg0: tensor<1x2xf32>) -> tensor<2x1xf32> { %0 = stablehlo.constant dense<2.000000e+00> : tensor<2x1xf32> %1 = stablehlo.transpose %arg0, dims = [1, 0] : (tensor<1x2xf32>) -> tensor<2x1xf32> %2 = stablehlo.add %1, %0 : tensor<2x1xf32> return %2 : tensor<2x1xf32> } // CHECK: %[[TRANSPOSE_0:.+]] = stablehlo.transpose
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 18 20:32:46 UTC 2024 - 14.6K bytes - Viewed (0)