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Results 41 - 50 of 87 for 8x1xf32 (0.12 sec)
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tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/include_variables_in_init_v1.py
# CHECK-NEXT: %[[READ_VAR_0:.*]] = "tf.ReadVariableOp"(%[[ARG_2]]) {{{.*}}} : (tensor<!tf_type.resource<tensor<1x3xf32>>>) -> tensor<1x3xf32> # CHECK-NEXT: %[[MATMUL_0:.*]] = "tf.MatMul"(%[[ARG_1]], %[[READ_VAR_0]]) <{{{.*}}}> {{{.*}}} : (tensor<3x1xf32>, tensor<1x3xf32>) -> tensor<3x3xf32> # CHECK-NEXT: return %[[MATMUL_0]] : tensor<3x3xf32> def Test(): x = tf.constant([[1.0], [1.0], [1.0]]) y = tf.compat.v1.get_variable( name='y',
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Oct 31 08:49:35 UTC 2023 - 3.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/tf_passes.td
```mlir %0 = "tf.Const"() {value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> %1 = "tf.Const"() {device = "", value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> %2 = "tf.Const"() {device = "baz", value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> ``` then running this pass with 'default-device=foobar', we get: ```mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 21:18:05 UTC 2024 - 99.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/tensorflow/tests/fallback_to_flex_ops_default.mlir
} // CHECK-LABEL: softmax func.func @softmax(%arg0: tensor<8x16xf32>) -> tensor<8x16xf32> { %0 = "tf.Softmax"(%arg0) : (tensor<8x16xf32>) -> tensor<8x16xf32> func.return %0 : tensor<8x16xf32> // CHECK: %[[CUSTOM_0:.*]] = "tfl.custom"(%arg0) <{custom_code = "FlexSoftmax", custom_option = #tfl<const_bytes : "0x07536F66746D617800161207536F66746D61781A002A070A0154120230013200000221191414042801">}> : (tensor<8x16xf32>) -> tensor<8x16xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 13.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/defun_export.py
# Verify that the function defined using function.Defun # has a corresponding tf.LegacyCall op. # CHECK: func {{@[a-zA-Z_0-9]+}}( # CHECK-SAME: [[ARG0:%.*]]: tensor<3x1xf32> {tf_saved_model.index_path = ["y"]}, # CHECK-SAME: [[ARG1:%.*]]: tensor<3x1xf32> {tf_saved_model.index_path = ["x"]} # # CHECK-NEXT: [[R0:%.*]] = "tf.LegacyCall"([[ARG1]], [[ARG0]]) z = plus(x, y)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Sep 28 21:37:05 UTC 2021 - 2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf-prefer-tf2xla.mlir
// NOFALLBACK-LABEL: @xla_svd func.func @xla_svd(%arg0: tensor<1x1xf32>) -> (tensor<1xf32>, tensor<1x1xf32>, tensor<1x1xf32>) { // NOFALLBACK: XlaSvd %s, %u, %v = "tf.XlaSvd"(%arg0) {max_iter = 1, epsilon = 1.0E-09 : f32, precision_config = ""} : (tensor<1x1xf32>) -> (tensor<1xf32>, tensor<1x1xf32>, tensor<1x1xf32>) func.return %s, %u, %v : tensor<1xf32>, tensor<1x1xf32>, tensor<1x1xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 15.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/tensorflow/tests/tf_to_quant_4bit.mlir
func.func @fakeQuantPerChannelForActivation(%arg0: tensor<8x3xf32>) -> (tensor<8x3xf32>) { %arg1 = arith.constant dense<[0.0, -1.0, 1.0]> : tensor<3xf32> %arg2 = arith.constant dense<[15.0, 14.0, 16.0]> : tensor<3xf32> %0 = "tf.FakeQuantWithMinMaxVarsPerChannel"(%arg0, %arg1, %arg2) {num_bits = 3, narrow_range = false} : (tensor<8x3xf32>, tensor<3xf32>, tensor<3xf32>) -> tensor<8x3xf32> func.return %0 : tensor<8x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 9.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/tensorflow/tests/tf_to_quant.mlir
func.func @fakeQuantPerChannelForActivation(%arg0: tensor<8x3xf32>) -> (tensor<8x3xf32>) { %arg1 = arith.constant dense<[0.0, -1.0, 1.0]> : tensor<3xf32> %arg2 = arith.constant dense<[255.0, 254.0, 256.0]> : tensor<3xf32> %0 = "tf.FakeQuantWithMinMaxVarsPerChannel"(%arg0, %arg1, %arg2) {num_bits = 5, narrow_range = false} : (tensor<8x3xf32>, tensor<3xf32>, tensor<3xf32>) -> tensor<8x3xf32> func.return %0 : tensor<8x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 9.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/shared_variable_v1.py
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/tensorflow/tests/tensor_list_ops_decomposition.mlir
%stack = "tf.TensorListStack"(%scatter, %elem_shape) : (tensor<!tf_type.variant<tensor<8x9xf32>>>, tensor<2xi32>) -> tensor<10x8x9xf32> // CHECK: return %[[SC]] : tensor<10x8x9xf32> func.return %stack : tensor<10x8x9xf32> } // ----- // Tests while loop.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 38.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/g3doc/_includes/tf_passes.md
For example, if we have the code ```mlir %0 = "tf.Const"() {value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> %1 = "tf.Const"() {device = "", value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> %2 = "tf.Const"() {device = "baz", value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> ``` then running this pass with 'default-device=foobar', we get: ```mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Aug 02 02:26:39 UTC 2023 - 96.4K bytes - Viewed (0)