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Results 1 - 10 of 26 for 3x11xf32 (0.12 sec)
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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) -
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/tfrt/tests/tf_to_corert/fallback.mlir
%1 = "tf.MatMul"(%arg0, %0) {T = f32, device = "/device:CPU:0", transpose_a = false, transpose_b = false} : (tensor<3x1xf32>, tensor<1x3xf32>) -> tensor<3x3xf32> func.return %1 : tensor<3x3xf32> } // CHECK-LABEL: func @gpu_device func.func @gpu_device(%arg0: tensor<3x1xf32>, %arg1: tensor<!tf_type.resource<tensor<1x3xf32>>>) -> tensor<3x3xf32> { // CHECK: {{%.*}} = corert.get_op_handler %arg0 "/device:GPU:0"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 00:18:59 UTC 2024 - 9.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tf_to_corert/device_conversion.mlir
func.return %2 : tensor<3x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 00:18:59 UTC 2024 - 645 bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tf_to_corert/basic.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 00:18:59 UTC 2024 - 3.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/shared_variable_v1.py
# CHECK: func {{@[a-zA-Z_0-9]+}}( # CHECK-SAME: [[ARG0:%.*]]: tensor<3x1xf32> {tf_saved_model.index_path = ["x"]}, # CHECK-SAME: [[ARG1:%.*]]: tensor<!tf_type.resource<tensor<1x3xf32>>> {tf_saved_model.bound_input = @[[VAR]]}) # CHECK-SAME: -> (tensor<3x3xf32> {tf_saved_model.index_path = ["r"]}) # CHECK-SAME: attributes {{.*}} tf_saved_model.exported_names = ["key"]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Oct 31 08:49:35 UTC 2023 - 2.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/ifrt/lower_to_ifrt_restore_variable.mlir
//expected-error@below {{'tf.ReluOp' op is not a supported user of RestoreV2Op}} %2 = "tf.ReluOp"(%0) : (tensor<3x1xf32>) -> tensor<3x1xf32> %1 = "tf.VarHandleOp"() <{container = "x", shared_name = "y"}> : () -> tensor<!tf_type.resource<tensor<3x1xf32>>> "tf.AssignVariableOp"(%1, %2) : (tensor<!tf_type.resource<tensor<3x1xf32>>>, tensor<3x1xf32>) -> () return } }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 31 20:44:15 UTC 2024 - 8.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/ifrt/tf_restore_pruning.mlir
%0 = "tf.RestoreV2"(%cst, %cst_1, %cst_0): (tensor<!tf_type.string>, tensor<1x!tf_type.string>, tensor<1x!tf_type.string>) -> tensor<3x1xf32> %1 = "tf.VarHandleOp"() <{container = "", shared_name = "y"}> : () -> tensor<!tf_type.resource<tensor<3x1xf32>>> "tf.AssignVariableOp"(%1, %0) : (tensor<!tf_type.resource<tensor<3x1xf32>>>, tensor<3x1xf32>) -> () return
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Mar 25 22:02:06 UTC 2024 - 1.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/unwrap_xla_call_module_op.mlir
func.func private @main_0(%arg0: tensor<10x1x3xf32>) -> tensor<3x10xf32> attributes {_from_xla_call_module} { %0 = stablehlo.reshape %arg0 : (tensor<10x1x3xf32>) -> tensor<3x10xf32> return %0 : tensor<3x10xf32> } // CHECK: %[[RESHAPE:.*]] = stablehlo.reshape // CHECK-NEXT: return %[[RESHAPE]] // CHECK: @main_1 func.func private @main_1(%arg0: tensor<3x10xf32>) -> tensor<6x5xf32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 08 22:40:14 UTC 2024 - 3.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/mlrt/rewrite_ifrt_load_variable.mlir
%0 = "tf.VarHandleOp"() <{container = "", shared_name = "y"}> : () -> tensor<!tf_type.resource<tensor<3x1xf32>>> %array_key, %tensor = "tf.IfrtLoadVariable"(%0) <{used_by_host = true}> : (tensor<!tf_type.resource<tensor<3x1xf32>>>) -> (tensor<!tf_type.string>, tensor<3x1xf32>) %1 = "tf.MatMul"(%arg0, %tensor) : (tensor<1x3xf32>, tensor<3x1xf32>) -> tensor<1x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 22 21:35:32 UTC 2024 - 1.7K bytes - Viewed (0)