@AastaLLL
I also see that Reduce is unsupported:
[ERROR] UFFParser: Parser error: scale1/moments/mean: Reduce operator not supported
ASSERT(parser->parse(uffFile.c_str(), network, nvinfer::DataType::kFLOAT)) failed at ros/src/tensorrt/EngineBuilder.cpp:119
Backtrace:
main in ??:0
__libc_start_main in /build/eglibc-SvCtMH/eglibc-2.19/csu/libc-start.c:321
_start in ??:0
This means all these operations are unsupported?
@tf2uff.register("Sum")
def convert_sum(name, tf_node, inputs, uff_graph, **kwargs):
return _reduce_helper(name, tf_node, inputs, uff_graph, func="sum", **kwargs)
@tf2uff.register("Prod")
def convert_prod(name, tf_node, inputs, uff_graph, **kwargs):
return _reduce_helper(name, tf_node, inputs, uff_graph, func="prod", **kwargs)
@tf2uff.register("Min")
def convert_min(name, tf_node, inputs, uff_graph, **kwargs):
return _reduce_helper(name, tf_node, inputs, uff_graph, func="min", **kwargs)
@tf2uff.register("Max")
def convert_max(name, tf_node, inputs, uff_graph, **kwargs):
return _reduce_helper(name, tf_node, inputs, uff_graph, func="max", **kwargs)
@tf2uff.register("Mean")
def convert_mean(name, tf_node, inputs, uff_graph, **kwargs):
return _reduce_helper(name, tf_node, inputs, uff_graph, func="mean", **kwargs)
@tf2uff.register("Squeeze")
def convert_squeeze(name, tf_node, inputs, uff_graph, **kwargs):
axis = tf2uff.get_tf_int_list(tf_node.attr['squeeze_dims'])
uff_graph.squeeze(inputs[0], name=name, axis=axis)
return [tf2uff.split_node_name_and_output(inp)[0] for inp in inputs]
Will they be enabled in the next release?