Wrong code in TF-TRT Instruction 2.2.4

Description

I realized that some code pieces in 2.2.4. TF-TRT 2.0 Workflow With A SavedModel are wrong. The code should be fixed as below (relevant lines were written bold).

import tensorflow as tf
from tensorflow.python.compiler.tensorrt import trt_convert as trt

conversion_params = trt.DEFAULT_TRT_CONVERSION_PARAMS
conversion_params = conversion_params._replace(
    max_workspace_size_bytes=(1<<32))
conversion_params = conversion_params._replace(precision_mode="FP16")
conversion_params = conversion_params._replace(

maximum_cached_engines=100) (engiens → engines)

converter = trt.TrtGraphConverterV2(
    input_saved_model_dir=input_saved_model_dir,
    conversion_params=conversion_params)
converter.convert()
def my_input_fn():
  for _ in range(num_runs):
    Inp1 = np.random.normal(size=(8, 16, 16, 3)).astype(np.float32)
    inp2 = np.random.normal(size=(8, 16, 16, 3)).astype(np.float32)
    yield inp1, inp2
converter.build(input_fn=my_input_fn)

converter.save(output_saved_model_dir) (new line for this part)

saved_model_loaded = tf.saved_model.load(
    output_saved_model_dir, tags=[tag_constants.SERVING])
graph_func = saved_model_loaded.signatures[
    signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY]
frozen_func = convert_to_constants.convert_variables_to_constants_v2(
    graph_func)
output = frozen_func(input_data)[0].numpy()

Hi @hb11,
Thank you for reporting this.
The team is checking and will update you on this.
Thanks!

Inp1 = np.random.normal(size=(8, 16, 16, 3)).astype(np.float32)
inp2 = np.random.normal(size=(8, 16, 16, 3)).astype(np.float32)
yield inp1, inp2

Seriously nVidia? Are you intentionally creating useless documentation to waste our time?!
How could code that doesn’t even execute possibly slip into official documentation?