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Posted to commits@tvm.apache.org by GitBox <gi...@apache.org> on 2021/09/22 19:57:34 UTC
[GitHub] [tvm] shashwat14 opened a new issue #9078: [Bug] Softmax in TFLite converter is channel first instead of channel last
shashwat14 opened a new issue #9078:
URL: https://github.com/apache/tvm/issues/9078
Compiled a TFLite toy model (conv + softmax) using TVM0.7 to generate a softmax output.
### Expected behavior
The uint8 output distribution of the output should look something like (below is tflite runtime output)
### Actual behavior
After I change axis to 3 [here](https://github.com/apache/tvm/blob/701d2c32759c95951c4eeca229addd1036539698/python/tvm/relay/frontend/tflite.py#L684), I get output that is similar to the expected output.
### Environment
OS: Ubuntu 20.04
TVM: 0.7
### Steps to reproduce
deps: tvm 0.7, numpy, and matplotlib to generate the plot
The zip contains the tflite model. Feel free to use a random
[tflite_model.tflite.zip](https://github.com/apache/tvm/files/7213238/tflite_model.tflite.zip)
[Here](https://drive.google.com/file/d/1FJLyOVhFbLNWElnqNu9Ur-ki3WEXWDdF/view?usp=sharing) is the input numpy array
```
import tvm
import numpy as np
import tflite
import tflite_runtime.interpreter as tflite_interpreter
from tvm import relay, transform
from tvm.contrib import graph_runtime as runtime
import matplotlib.pyplot as plt
def generate_hist(x, title, filename):
plt.title(title)
plt.xlabel('uint8 value')
plt.xlim([-1,256])
plt.ylabel('frequency')
H, bins = np.histogram(x.flatten(), bins=256, range=(0,256))
plt.bar(bins[:-1], H)
plt.savefig(filename)
plt.clf()
# TFLite compilation
model_path = 'tflite_model.tflite'
interpreter = tflite_interpreter.Interpreter(model_path=model_path)
interpreter.allocate_tensors()
input_details = interpreter.get_input_details()
output_details = interpreter.get_output_details()
with open('conv_softmax_input.bin', 'rb') as f:
input_arr = np.load(f) * 255
input_data = input_arr.astype(np.uint8)
interpreter.set_tensor(input_details[0]['index'], input_data)
interpreter.invoke()
tflite_output1 = interpreter.get_tensor(output_details[0]['index'])
# TVM Compilation
tflite_model_buf = open(model_path, "rb").read()
tflite_model = tflite.Model.GetRootAsModel(tflite_model_buf, 0)
input_dict={"input":(1,100,160,256)}
input_dtype = {"input":"uint8"}
mod, params = relay.frontend.from_tflite(
tflite_model, shape_dict=input_dict, dtype_dict=input_dtype
)
target = "llvm"
with transform.PassContext(opt_level=2):
lib = relay.build(mod, target, params=params)
#invokes pure TVM compilation
module = runtime.GraphModule(lib["default"](tvm.cpu()))
module.set_input("input", tvm.nd.array(input_data))
module.run()
tvm_output1 = module.get_output(0).asnumpy()
generate_hist(tflite_output1, 'tflite quant(uint8) hist', 'tflite_hist.png')
generate_hist(tvm_output1, 'tvm quant(uint8) hist', 'tvm_hist.png')
```
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[GitHub] [tvm] shashwat14 removed a comment on issue #9078: [Bug] Softmax in TFLite converter is channel first instead of channel last
Posted by GitBox <gi...@apache.org>.
shashwat14 removed a comment on issue #9078:
URL: https://github.com/apache/tvm/issues/9078#issuecomment-926806805
I think the axis is hard coded to 1 assuming the task is a simple classification task. However, the softmax can occur over any axis. In the above example it occurs for every "pixel" where each pixel has 14 dimensions. The axis parameter should always represent the channel index (unless overridden by the user). In numpy notation, axis can be -1 for most cases.
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[GitHub] [tvm] shashwat14 commented on issue #9078: [Bug] Softmax in TFLite converter is channel first instead of channel last
Posted by GitBox <gi...@apache.org>.
shashwat14 commented on issue #9078:
URL: https://github.com/apache/tvm/issues/9078#issuecomment-926806805
I think the axis is hard coded to 1 assuming the task is a simple classification task. However, the softmax can occur over any axis. In the above example it occurs for every "pixel" where each pixel has 14 dimensions. The axis parameter should always represent the channel index (unless overridden by the user). In numpy notation, axis can be -1 for most cases.
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[GitHub] [tvm] masahi closed issue #9078: [Bug] Softmax in TFLite converter is channel first instead of channel last
Posted by GitBox <gi...@apache.org>.
masahi closed issue #9078:
URL: https://github.com/apache/tvm/issues/9078
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