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Results 11 - 20 of 89 for 5x6xf32 (0.17 sec)
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tensorflow/compiler/mlir/tensorflow/tests/mlir2graphdef/derived_size_attr.mlir
%input:2 = tf_executor.island wraps "tf.Const"() {dtype = "tftype$DT_INT32", value = dense<1.0> : tensor<4x6xf32>} : () -> tensor<4x6xf32> %split:3 = tf_executor.island wraps "tf.Split"(%dim#0, %input#0) : (tensor<i32>, tensor<4x6xf32>) -> (tensor<2x6xf32>, tensor<2x6xf32>) tf_executor.fetch } func.return
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Mar 28 12:06:33 UTC 2022 - 700 bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/multi_arguments_results_v1.py
# CHECK-LABEL: func @key( # CHECK-SAME: %[[ARG0:.*]]: tensor<3x5xf32> {tf_saved_model.index_path = ["y"]} # CHECK-SAME: %[[ARG1:.*]]: tensor<5x3xf32> {tf_saved_model.index_path = ["x"]} # CHECK-SAME: tensor<3x3xf32> {tf_saved_model.index_path = ["t"]} # CHECK-SAME: tensor<5x5xf32> {tf_saved_model.index_path = ["s"]} # CHECK-SAME: attributes {{.*}} tf_saved_model.exported_names = ["key"]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Sep 28 21:37:05 UTC 2021 - 3.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tpu_sharding_identification.mlir
} func.func @_func(%arg0: tensor<2x4xf32>, %arg1: tensor<4x2xf32>) -> tensor<2x2xf32> { %0 = "tf.MatMul"(%arg0, %arg1) {_XlaSharding = "\08\03\1A\02\02\01\22\02\00\01"} : (tensor<2x4xf32>, tensor<4x2xf32>) -> tensor<2x2xf32> %1 = "tf.Identity"(%0) : (tensor<2x2xf32>) -> tensor<2x2xf32> return %1 : tensor<2x2xf32> } // ----- // The following op sharding is used in the following test case:
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/lite/tests/quantize-dynamic-range-float16.mlir
time_major = false} : ( tensor<1x2x3xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, none, none, none, tensor<3xf32>, tensor<3xf32>, tensor<3xf32>, tensor<3xf32>, none, none, tensor<1x3xf32>, tensor<1x3xf32>, none, none, none, none) -> 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) -
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/tests/prepare-quantize-post-training-16bits.mlir
time_major = false} : ( tensor<1x2x3xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, none, none, none, tensor<3xf32>, tensor<3xf32>, tensor<3xf32>, tensor<3xf32>, none, none, tensor<1x3xf32>, tensor<1x3xf32>, none, none, none, none) -> tensor<1x2x3xf32>
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/tfrt/tests/ifrt/rewrite_cluster_to_ifrt_call.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Feb 17 07:28:40 UTC 2024 - 9K 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/quantization/tensorflow/tests/insert_custom_aggregation_ops.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 32.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/ifrt/sink_variable_as_named_array.mlir
// CHECK-NEXT: return [[RES]], [[MATRES]] : tensor<1x1xf32>, tensor<1x1xf32> // module { func.func @serving_default(%arg0: tensor<1x3xf32>) -> (tensor<1x1xf32>, tensor<1x1xf32>) { %0 = "tf.VarHandleOp"() <{container = "", shared_name = "y"}> : () -> tensor<!tf_type.resource<tensor<3x1xf32>>> %2 = "tf.ReadVariableOp"(%0) : (tensor<!tf_type.resource<tensor<3x1xf32>>>) -> tensor<3x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 15:33:17 UTC 2024 - 5.3K bytes - Viewed (0)