def test_graph_calc_quantized8_qnoq(mnist_unfused_8bit_state, mnist_images):
G = load_state(mnist_unfused_8bit_state)
input_tensor = import_data(mnist_images[0],
height=28,
width=28,
offset=0,
divisor=255)
input_tensor = input_tensor.reshape((28, 28, 1))
executer = GraphExecuter(G, qrecs=G.quantization)
diffs = []
for step_idx, pnode, output, details, qoutput, qdetails, fnode in\
executer.execute_qnoq_iterator([input_tensor]):
del step_idx, pnode, details, qdetails, fnode
diffs.append(output[0] - qoutput[0])
assert np.max(np.abs(diffs[7])) < 9
def _collect_execution(self, G, tensors, qrecs):
outputs = []
fusion_outputs = []
executer = GraphExecuter(G, qrecs)
for step_idx, node, output, details, qoutput, qdetails, fusion_node in\
executer.execute_qnoq_iterator(tensors):
output = [np.copy(out) for out in output]
qoutput = [np.copy(out) for out in qoutput]
if fusion_node:
fusion_outputs.append({
"name":
"",
"step_idx":
"{}_{}".format(step_idx, len(fusion_outputs)),
"node":
fusion_node,
"output":
output,
"details":
details,
"qoutput":
qoutput,
"qdetails":
qdetails
})
else:
stat = {
"name": node.name,
"step_idx": str(step_idx),
"node": node,
"output": output,
"details": details,
"qoutput": qoutput,
"qdetails": qdetails,
"fusion_outputs": []
}
if len(fusion_outputs) > 0:
stat['fusion_outputs'] = fusion_outputs.copy()
fusion_outputs.clear()
outputs.append(stat)
return outputs
