- Sort Score
- Result 10 results
- Languages All
Results 21 - 30 of 63 for tape_ (0.1 sec)
-
tensorflow/c/eager/gradients_internal.h
ForwardOperation*); // Make the call to `Tape::RecordOperation`. Status Execute(AbstractOperation*, AbstractContext*, absl::Span<AbstractTensorHandle*> retvals, int* num_retvals, ForwardOperation*, Tape*, const GradientRegistry&); } // namespace internal } // namespace gradients } // namespace tensorflow
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sun Oct 24 11:27:35 UTC 2021 - 4.2K bytes - Viewed (0) -
tensorflow/c/eager/gradients.cc
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 15 09:49:45 UTC 2024 - 19.3K bytes - Viewed (0) -
fastapi/openapi/models.py
openIdConnect = "openIdConnect" class SecurityBase(BaseModelWithConfig): type_: SecuritySchemeType = Field(alias="type") description: Optional[str] = None class APIKeyIn(Enum): query = "query" header = "header" cookie = "cookie" class APIKey(SecurityBase): type_: SecuritySchemeType = Field(default=SecuritySchemeType.apiKey, alias="type")
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Thu Apr 18 22:49:33 UTC 2024 - 15K bytes - Viewed (0) -
src/main/resources/fess_indices/fess/lv/stopwords.txt
ar diezin droši diemžēl nebūt ik it taču nu pat tiklab iekšpus nedz tik nevis turpretim jeb iekam iekām iekāms kolīdz līdzko tiklīdz jebšu tālab tāpēc nekā itin jā jau jel nē nezin tad tikai vis tak iekams vien # modal verbs būt biju biji bija bijām bijāt esmu esi esam esat
Registered: Wed Jun 12 13:08:18 UTC 2024 - Last Modified: Thu Jul 19 06:31:02 UTC 2018 - 1.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/python/tfr_gen.py
return default if len(types_) == 1: type_, = types_ else: type_ = types_ if default is not None and type_ != default: print('WARN: type annotation {}({}) does not match {}({})'.format( type_, type(type_), default, type(default))) self.debug_print(node) return type_ def _pack_tensor_list(self, value):
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 27 15:27:03 UTC 2022 - 55.8K bytes - Viewed (0) -
src/runtime/defs_windows.go
} type memoryBasicInformation struct { baseAddress uintptr allocationBase uintptr allocationProtect uint32 regionSize uintptr state uint32 protect uint32 type_ uint32 } // https://learn.microsoft.com/en-us/windows-hardware/drivers/ddi/wdm/ns-wdm-_osversioninfow type _OSVERSIONINFOW struct { osVersionInfoSize uint32 majorVersion uint32
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Thu Mar 21 11:49:46 UTC 2024 - 2.5K bytes - Viewed (0) -
tensorflow/c/eager/parallel_device/parallel_device_testlib.h
// // Note that creating this resource-dtype handle can fail, so `Create` is a // separate static method which returns a status. Variable(TFE_TensorHandle* handle, TF_DataType type) : handle_(handle), type_(type) {} // Helper for constructing a resource handle and wrapping it in a `Variable` // object. static Variable* Create(TFE_Context* context, TF_DataType type,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Feb 09 01:12:35 UTC 2021 - 6.9K bytes - Viewed (0) -
tests/test_compat.py
from fastapi._compat import is_pv1_scalar_field field_info = FieldInfo() field = ModelField( name="foo", field_info=field_info, type_=Union[str, List[int]], class_validators={}, model_config=BaseConfig, ) assert not is_pv1_scalar_field(field) @needs_pydanticv2 def test_get_model_config():
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Thu Sep 28 04:14:40 UTC 2023 - 2.8K bytes - Viewed (0) -
tensorflow/c/eager/tracing_utils.cc
==============================================================================*/ #include "tensorflow/c/eager/tracing_utils.h" #include "tensorflow/c/eager/c_api_unified_experimental_internal.h" #include "tensorflow/c/experimental/gradients/tape/tape_operation.h" #include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h" #include "tensorflow/core/platform/errors.h" namespace tensorflow { namespace tracing {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Feb 27 13:57:45 UTC 2024 - 1.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/examples/mnist/mnist_train.py
labels = tf.one_hot(features['label'], num_classes) with tf.GradientTape() as tape: logits = model(inputs) loss_value = tf.reduce_mean( tf.nn.softmax_cross_entropy_with_logits(labels, logits)) grads = tape.gradient(loss_value, model.trainable_variables) correct_prediction = tf.equal(tf.argmax(logits, 1), tf.argmax(labels, 1))
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Oct 20 03:05:18 UTC 2021 - 6.5K bytes - Viewed (0)