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tensorflow/c/eager/gradient_checker.cc
namespace gradients { using namespace std; // ================== Helper functions ================= // Fills data with values [start,end) with given step size. void Range(vector<int32_t>* data, int32_t start, int32_t end, int32_t step = 1) { for (int32_t i = start; i < end; i += step) { (*data)[i] = i; } } // Fills out_dims with the dimensions of the given tensor. void GetDims(const TF_Tensor* t, int64_t* out_dims) {
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/dlpack.cc
case TF_DataType::TF_FLOAT: case TF_DataType::TF_DOUBLE: dtype.code = DLDataTypeCode::kDLFloat; break; case TF_DataType::TF_INT8: case TF_DataType::TF_INT16: case TF_DataType::TF_INT32: case TF_DataType::TF_INT64: dtype.code = DLDataTypeCode::kDLInt; break; case TF_DataType::TF_UINT8: case TF_DataType::TF_UINT16: case TF_DataType::TF_UINT32:
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 12.8K bytes - Viewed (0) -
tensorflow/c/c_api_experimental_test.cc
TFE_Op* reshape_op = TFE_NewOp(tfe_context_, "Reshape", status_); CHECK_EQ(TF_OK, TF_GetCode(status_)) << TF_Message(status_); TFE_OpSetAttrType(reshape_op, "T", TF_FLOAT); TFE_OpSetAttrType(reshape_op, "Tshape", TF_INT32); CheckOutputShapes(reshape_op, /* input_shapes*/ {unknown_shape(), unknown_shape()}, /* input_tensors*/ {nullptr, tensor_1X6},
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Jan 17 22:27:52 GMT 2023 - 13.1K bytes - Viewed (1) -
tensorflow/c/experimental/next_pluggable_device/tensor_pjrt_buffer_util_test.cc
} auto pjrt_client = xla::GetCApiClient(DEVICE_CPU); CHECK_OK(pjrt_client.status()); auto c_api_client = down_cast<xla::PjRtCApiClient*>(pjrt_client->get()); std::vector<int32_t> data(1, 0); xla::Shape shape = xla::ShapeUtil::MakeShape(xla::S32, {1}); auto buffer = c_api_client->pjrt_c_client()->client->BufferFromHostBuffer( data.data(), shape.element_type(), shape.dimensions(),
C++ - Registered: Tue Feb 27 12:39:08 GMT 2024 - Last Modified: Mon Oct 30 19:20:20 GMT 2023 - 7.2K bytes - Viewed (0) -
tensorflow/c/eager/c_api.h
// will be blocked till the copy completes. This is the default placement // policy. TFE_DEVICE_PLACEMENT_SILENT = 2, // Placement policy which silently copies int32 tensors but not other dtypes. TFE_DEVICE_PLACEMENT_SILENT_FOR_INT32 = 3, } TFE_ContextDevicePlacementPolicy; // LINT.ThenChange(//tensorflow/c/eager/immediate_execution_context.h) // Sets the default execution mode (sync/async). Note that this can be
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Apr 27 21:07:00 GMT 2023 - 22.8K bytes - Viewed (1) -
tensorflow/c/experimental/filesystem/plugins/posix/posix_filesystem.cc
while (n > 0) { // Some platforms, notably macs, throw `EINVAL` if `pread` is asked to read // more than fits in a 32-bit integer. size_t requested_read_length; if (n > INT32_MAX) requested_read_length = INT32_MAX; else requested_read_length = n; // `pread` returns a `ssize_t` on POSIX, but due to interface being // cross-platform, return type of `Read` is `int64_t`.
C++ - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Sun Mar 24 20:08:23 GMT 2024 - 15.8K bytes - Viewed (0) -
tensorflow/c/eager/c_api_test.cc
EXPECT_EQ(attr_found->second.type(), tensorflow::DataType::DT_FLOAT); attr_found = attr_values.find("Tidx"); EXPECT_NE(attr_found, attr_values.cend()); EXPECT_EQ(attr_found->second.type(), tensorflow::DataType::DT_INT32); TFE_TensorHandle* retvals[1] = {nullptr}; int num_retvals = 1; TFE_Execute(minOp, &retvals[0], &num_retvals, status); 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) -
ci/official/containers/linux_arm64/builder.devtoolset/gcc9-fixups.patch
index e54a067..215b0e0 100644 --- a/sysdeps/ieee754/flt-32/k_rem_pio2f.c +++ b/sysdeps/ieee754/flt-32/k_rem_pio2f.c @@ -65,7 +65,8 @@ int __kernel_rem_pio2f(float *x, float *y, int e0, int nx, int prec, const int32 /* compute q[0],q[1],...q[jk] */ for (i=0;i<=jk;i++) { - for(j=0,fw=0.0;j<=jx;j++) fw += x[j]*f[jx+i-j]; q[i] = fw; + for(j=0,fw=0.0;j<=jx;j++) fw += x[j]*f[jx+i-j]; + q[i] = fw; }
Others - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Mon Sep 18 14:52:45 GMT 2023 - 8.9K bytes - Viewed (0) -
tensorflow/c/eager/c_api_test_util.h
TFE_Op* RecvOp(TFE_Context* ctx, const std::string& op_name, const std::string& send_device, const std::string& recv_device, tensorflow::uint64 send_device_incarnation); // Return a 1-D INT32 tensor containing a single value 1. TFE_TensorHandle* TestAxisTensorHandle(TFE_Context* ctx); // Return an op taking minimum of `input` long `axis` dimension. TFE_Op* MinOp(TFE_Context* ctx, TFE_TensorHandle* input,
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Jul 17 23:43:59 GMT 2023 - 7.7K bytes - Viewed (0) -
tensorflow/c/eager/parallel_device/parallel_device_lib.cc
} std::unique_ptr<ParallelTensor> ParallelDevice::DeviceIDs( TFE_Context* context, TF_Status* status) const { std::vector<int32_t> ids; ids.reserve(num_underlying_devices()); for (int i = 0; i < num_underlying_devices(); ++i) { ids.push_back(i); } return ScalarsFromSequence<int32_t>(ids, context, status); } absl::optional<std::vector<std::unique_ptr<ParallelTensor>>>
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Fri Feb 09 07:47:20 GMT 2024 - 25.4K bytes - Viewed (1)