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Results 11 - 20 of 85 for conv3d (0.14 sec)
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tensorflow/compiler/mlir/quantization/tensorflow/tests/add_quantization_unit_loc.mlir
%2 = "tf.Cast"(%1) {Truncate = false} : (tensor<1x3x2x2xbf16>) -> tensor<1x3x2x2xf32> %3 = "tf.IdentityN"(%2) {device = ""} : (tensor<1x3x2x2xf32>) -> tensor<1x3x2x2xf32> return %3 : tensor<1x3x2x2xf32> // CHECK: tf.Conv2D // CHECK-SAME: loc(callsite("Model/conv2d@conv2d_with_valid_loc"("Conv2D") at "QuantizationUnit({{.*}})")) }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Oct 03 02:39:10 UTC 2023 - 3.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/lift_quantizable_spots_as_functions_xla_selective_quantization.mlir
%1 = "tf.Conv2D"(%0, %cst) {data_format = "NHWC", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 2, 1], use_cudnn_on_gpu = true} : (tensor<1x3x4x3xf32>, tensor<2x3x3x2xf32>) -> tensor<1x3x2x2xf32> loc(fused["Conv2D:", "Model/conv2d"]) %2 = "tf.IdentityN"(%1) {device = ""} : (tensor<1x3x2x2xf32>) -> tensor<1x3x2x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 6.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_to_nchw.mlir
// Check that Conv2D computed in NCHW format, and all redundant transpose // operations removed from the function. // CHECK: %[[CONV:[0-9]*]] = "tf.Conv2D"(%arg0, %arg1) // CHECK-SAME: data_format = "NCHW" // CHECK-SAME: -> tensor<1x8x32x32xf32> // CHECK: return %[[CONV]] func.return %4 : tensor<1x8x32x32xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 24 05:47:26 UTC 2022 - 1.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/fake_quant_e2e_xla.mlir
return %3 : tensor<?x?x?x2xf32> } // CHECK-LABEL: func @conv_with_dynamic_shape // The Conv2D should not be quantized since it has dynamic channel. // CHECK: "tf.Conv2D" // CHECK-SAME: (tensor<?x?x?x?xf32>, tensor<2x3x3x2xf32>) -> tensor<?x?x?x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 7.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_to_nhwc.mlir
%5 = "tf.Conv2D"(%4, %arg3) { data_format = "NCHW", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "VALID", strides = [1, 1, 2, 2] } : (tensor<?x3x230x230xf32>, tensor<7x7x3x64xf32>) -> tensor<?x64x112x112xf32> // CHECK: %[[CONV0:[0-9]*]] = "tf.Conv2D" // CHECK-SAME: %[[PAD]]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 7.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_layout_assignment_to_nchw.mlir
// CHECK: %[[ARG_PERM:.*]] = "tf.Const"() <{value = dense<[0, 3, 1, 2]> : tensor<4xi64>}> // CHECK: %[[ARG_TRANSPOSE:[0-9]*]] = "tf.Transpose"(%arg0, %[[ARG_PERM]]) // CHECK: %[[CONV2D:[0-9]*]] = "tf.Conv2D"(%[[ARG_TRANSPOSE]], %arg1) // CHECK-SAME: data_format = "NCHW" // CHECK-SAME: dilations = [1, 4, 2, 3] // CHECK-SAME: explicit_paddings = [1, 2, 7, 8, 3, 4, 5, 6] // CHECK-SAME: padding = "EXPLICIT"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_layout_assignment_gpu_cc_70.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 21 08:41:18 UTC 2022 - 8.5K bytes - Viewed (0) -
test/typeparam/issue49027.dir/a.go
package a func Conv(v interface{}) string { return conv[string](v) } func conv[T any](v interface{}) T { return v.(T) } func Conv2(v interface{}) (string, bool) { return conv2[string](v) } func conv2[T any](v interface{}) (T, bool) { x, ok := v.(T) return x, ok } func Conv3(v interface{}) string { return conv3[string](v) }
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Tue Oct 19 22:47:48 UTC 2021 - 871 bytes - Viewed (0) -
src/sync/cond.go
// a call to [Cond.Broadcast] or [Cond.Signal] “synchronizes before” any Wait call // that it unblocks. // // For many simple use cases, users will be better off using channels than a // Cond (Broadcast corresponds to closing a channel, and Signal corresponds to // sending on a channel). // // For more on replacements for [sync.Cond], see [Roberto Clapis's series on
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Fri Jun 07 21:14:51 UTC 2024 - 4.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/optimize.mlir
// CHECK-DAG: %[[cst:.*]] = "tf.Const{{.*}} dense<8.000000e+00> : tensor<3x3x3x16xf32> // CHECK-DAG: %[[cst_0:.*]] = "tf.Const{{.*}} dense<1.200000e+01> : tensor<16xf32> // CHECK-NEXT: %[[conv:.*]] = "tf.Conv2D"(%arg0, %[[cst]]) // CHECK-NEXT: %[[bias:.*]] = "tf.AddV2"(%[[conv]], %[[cst_0]]) // CHECK-NEXT: return %[[bias]] : tensor<256x8x7x16xf32> } // CHECK-LABEL: convaddv2mul
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 3.3K bytes - Viewed (0)