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Results 1 - 5 of 5 for tfdtype$DT_INT32 (0.18 sec)
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tensorflow/compiler/mlir/tensorflow/tests/decompose_resource_ops.mlir
// ALWAYS-DECOMPOSE-NOT: "tf.AssignAddVariableOp" "tf.AssignAddVariableOp"(%0, %1) {dtype = "tfdtype$DT_INT32"} : (tensor<*x!tf_type.resource<tensor<2x8xi32>>>, tensor<i32>) -> () // CHECK: tf_device.cluster "tf_device.cluster"() ({ // CHECK-NOT: "tf.AssignAddVariableOp" "tf.AssignAddVariableOp"(%0, %1) {dtype = "tfdtype$DT_INT32"} : (tensor<*x!tf_type.resource<tensor<2x8xi32>>>, tensor<i32>) -> () tf_device.return }) : () -> ()
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 22 19:47:48 UTC 2024 - 51.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/constant-fold.mlir
%0 = "tf.Shape"(%arg0) {T = "tfdtype$DT_FLOAT", output = "tfdtype$DT_INT32"} : (tensor<f32>) -> tensor<0xi32> // Result shape need not be static. Folding harness uses TensorFlow constant // in that case. // CHECK-DAG: "tf.Const"() <{value = dense<[1, 32, 32, 16]> : tensor<4xi32>}> : () -> tensor<?xi32> %1 = "tf.Shape"(%arg1) {T = "tfdtype$DT_FLOAT", output = "tfdtype$DT_INT32"} : (tensor<1x32x32x16xf32>) -> tensor<?xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jan 31 23:22:24 UTC 2024 - 36.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/legalize-tf.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 05 01:54:33 UTC 2024 - 153.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf.mlir
// ----- // CHECK-LABEL: @const func.func @const() -> tensor<2xi32> { // CHECK: mhlo.constant dense<0> : tensor<2xi32> %0 = "tf.Const"() {device = "", name = "", dtype = "tfdtype$DT_INT32", value = dense<0> : tensor<2xi32>} : () -> (tensor<2xi32>) func.return %0: tensor<2xi32> } // ----- // CHECK-LABEL: @const_dynamic_output func.func @const_dynamic_output() -> tensor<*xi32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 06 18:46:23 UTC 2024 - 335.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/shape_inference.mlir
// CHECK: tf.BroadcastGradientArgs // CHECK-SAME: (tensor<*xi32>, tensor<0xi32>) -> (tensor<?xi32>, tensor<?xi32>) %2:2 = "tf.BroadcastGradientArgs"(%arg0, %arg1) {T = "tfdtype$DT_INT32", name = "BroadcastGradientArgs"} : (tensor<*xi32>, tensor<0xi32>) -> (tensor<?xi32>, tensor<?xi32>) func.return %2#0 : tensor<?xi32> } // CHECK-LABEL: func @shape_from_const_input
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jan 23 17:24:10 UTC 2024 - 167.4K bytes - Viewed (0)