Closed suyash-narain closed 1 month ago
If you don't even provide a partial ONNX, I have no idea what kind of mistake you are making. I will not answer the question because it is a waste of survey time unless a small portion of the model entrance, not the entire model, is shared with me.
You are definitely using tf2onnx
in the wrong way.
my apologies. i thought the model url was shared by me already please find the model url attached: https://catalog.ngc.nvidia.com/orgs/nvidia/teams/tao/models/bodyposenet/files?version=deployable_onnx_v1.0.1 model name: model.onnx
NVIDIA engineers' use of tf2onnx
is totally useless.
sor4onnx \
--input_onnx_file_path model.onnx \
--old_new ":0" "" \
--mode full \
--search_mode suffix_match \
--output_onnx_file_path model_renamed.onnx
onnx2tf -i model_renamed.onnx -ois input_1:1,224,320,3 -kat input_1
thank you for your prompt reply. I am using onnx2tf.convert using python API to automate the conversion. can you tell me what are the corresponding arguments which i can use instead of kat when using onnx2tf.convert() function in python?
thanks for your help
There is no such method; it is correct to convert to NCHW at the point of generating ONNX.
okay thank you.
Issue Type
Others
OS
Linux
onnx2tf version number
1.22.4
onnx version number
1.15.0
onnxruntime version number
1.17.1
onnxsim (onnx_simplifier) version number
0.4.35
tensorflow version number
2.16.1
Download URL for ONNX
None
Parameter Replacement JSON
Description
keep_nwc_or_nhwc_or_ndhwc_input_names=['input_1:0']
keep_ncw_or_nchw_or_ncdhw_input_names=['input_1:0']
andkeep_shape_absolutely_input_names=['input_1:0']
in my python script when calling onnx2tf.convert. The converted tflite model still has the shape (1,320,3,224)what am I doing wrong here? Am i missing something? i want the input shape to remain constant. its jumbling the input shape and then inserting the transpose op to change the shape to NHWC (1,224,320,3). thanks