Sparsity-aware deep learning inference runtime for CPUs
This is a patch release for 1.3.0 that contains the following changes:
This is a patch release for 1.3.0 that contains the following changes:
default_precision
parameter in the configuration file.engine
class.warn
.axes
parameter to be specified either as an input or an attribute in several ONNX operators.time.perf_counter
for more accurate benchmarks.num_streams
provided to the engine_context_t
is greater than the number of physical CPU cores.num_streams
provided to the engine_context_t
is greater than the number of physical CPU cores.This is a patch release for 1.0.0 that contains the following changes:
This is a patch release for 1.0.0 that contains the following changes:
Crashes with an assertion failure no longer happen in the following cases:
num_streams
parameter to fewer than the number of NUMA nodes.The engine no longer enters an infinite loop when an operation has multiple inputs coming from the same source.
Error messaging improved for installation failures of non-supported operating systems.
Supported transformers datasets
version capped for compatibility with pipelines.
num_streams
argument to tune the number of requests that are processed in parallel.num_streams
parameter to fewer than the number of NUMA nodes; hotfix forthcoming.This is a patch release for 0.12.0 that contains the following changes: