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tensorflow/c/eager/c_api_unified_experimental_graph.cc
ArraySlice<const bool>(b.get(), num_values)); return absl::OkStatus(); } Status SetAttrShapeList(const char* attr_name, const int64_t** dims, const int* num_dims, int num_values) override { std::vector<PartialTensorShape> shapes; shapes.reserve(num_values); for (int i = 0; i < num_values; ++i) { if (num_dims[i] < 0) { shapes.emplace_back();
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Mar 12 20:00:09 GMT 2024 - 15.4K bytes - Viewed (1) -
tensorflow/c/eager/c_api_unified_experimental.cc
void TF_DeleteOutputList(TF_OutputList* o) { delete unwrap(o); } void TF_OutputListSetNumOutputs(TF_OutputList* o, int num_outputs, TF_Status* s) { unwrap(o)->expected_num_outputs = num_outputs; unwrap(o)->outputs.clear(); unwrap(o)->outputs.resize(num_outputs); } int TF_OutputListNumOutputs(TF_OutputList* o) { return unwrap(o)->outputs.size(); }
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 9K bytes - Viewed (0) -
tensorflow/c/eager/c_api_test.cc
TFE_DeleteContext(ctx); EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status); const int num_devices = TF_DeviceListCount(devices); EXPECT_GE(num_devices, 1) << "At least one CPU device should exist"; for (int i = 0; i < num_devices; ++i) { EXPECT_NE("", TF_DeviceListName(devices, i, status)) << i; EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status); }
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Aug 03 20:50:20 GMT 2023 - 94.6K bytes - Viewed (1) -
tensorflow/c/eager/abstract_operation.h
virtual Status SetAttrTypeList(const char* attr_name, const DataType* values, int num_values) = 0; virtual Status SetAttrBoolList(const char* attr_name, const unsigned char* values, int num_values) = 0; virtual Status SetAttrShapeList(const char* attr_name, const int64_t** dims,
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Wed Jul 14 16:20:41 GMT 2021 - 6.8K bytes - Viewed (0) -
tensorflow/c/c_api.cc
int num_shapes) { std::vector<PartialTensorShape> shapes; shapes.reserve(num_shapes); for (int i = 0; i < num_shapes; ++i) { if (num_dims[i] < 0) { shapes.emplace_back(); } else { shapes.emplace_back(ArraySlice<int64_t>( reinterpret_cast<const int64_t*>(dims[i]), num_dims[i])); } }
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 03:35:10 GMT 2024 - 102.3K bytes - Viewed (0) -
src/test/java/org/codelibs/fess/it/search/SearchApiTests.java
} @Test public void searchTestWith1Word() throws Exception { String query = "java"; Map<String, String> params = new HashMap<>(); params.put("q", query); params.put("num", "100"); String response = checkMethodBase(new HashMap<>()).params(params).get("/api/v1/documents").asString(); assertTrue(JsonPath.from(response).getInt("record_count") > 0);
Java - Registered: Mon May 06 08:04:11 GMT 2024 - Last Modified: Thu Feb 22 01:37:57 GMT 2024 - 18.6K bytes - Viewed (1) -
tensorflow/c/eager/gradient_checker.cc
// Will sum all dimensions, so get a Tensor containing [0,...,num_dims_out-1]. AbstractTensorHandlePtr sum_dims; { vector<int32_t> vals(num_dims_out); int64_t vals_shape[] = {num_dims_out}; Range(&vals, 0, num_dims_out); AbstractTensorHandle* sum_dims_raw = nullptr; TF_RETURN_IF_ERROR(TestTensorHandleWithDims<int32_t, TF_INT32>( ctx, vals.data(), vals_shape, 1, &sum_dims_raw)); sum_dims.reset(sum_dims_raw); }
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 7.3K bytes - Viewed (0) -
tensorflow/c/eager/gradients_internal.h
ForwardOperation*); Status SetAttrBoolList(AbstractOperation*, const char* attr_name, const unsigned char* values, int num_values, ForwardOperation*); Status SetAttrShapeList(AbstractOperation*, const char* attr_name, const int64_t** dims, const int* num_dims, int num_values, ForwardOperation*);
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Sun Oct 24 11:27:35 GMT 2021 - 4.2K bytes - Viewed (0) -
tensorflow/c/eager/parallel_device/parallel_device_testlib.cc
TF_Status* status) { const int num_bytes = v.size() * sizeof(float); float* values = new float[v.size()]; memcpy(values, v.data(), num_bytes); int64_t dims = v.size(); std::unique_ptr<TF_Tensor, decltype(&TF_DeleteTensor)> tensor( TF_NewTensor(TF_FLOAT, &dims, 1 /* num_dims */, values, num_bytes, &FloatDeallocator, nullptr), TF_DeleteTensor);
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Jun 15 15:44:44 GMT 2021 - 12.5K bytes - Viewed (0) -
tensorflow/c/eager/parallel_device/parallel_device_testlib.h
// Helper to un-pack `num_replicas` TFE_TensorHandles from one parallel handle. template <std::size_t num_replicas> void ExtractPerDeviceValues( TFE_Context* context, TFE_TensorHandle* input, std::array<TensorHandlePtr, num_replicas>* components, TF_Status* status); // Helper to pack `num_replicas` TFE_TensorHandles into one parallel handle. template <std::size_t num_replicas> TensorHandlePtr CreatePerDeviceValues(
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Feb 09 01:12:35 GMT 2021 - 6.9K bytes - Viewed (0)