def test_default_min_max_length():
happy_tt = HappyTextToText()
args = TTSettings(min_length=5, max_length=5)
output = happy_tt.generate_text(
"translate English to French: Hello my name is Eric", args=args)
tokens = happy_tt.tokenizer.encode(output.text, return_tensors="pt")
length = len(tokens[0])
assert length == 5
def example_7_1():
# --------------------------------------#
happy_tt = HappyTextToText() # default uses t5-small
top_p_sampling_settings = TTSettings(do_sample=True,
top_k=0,
top_p=0.8,
temperature=0.7,
min_length=20,
max_length=20,
early_stopping=True)
result = happy_tt.generate_text(
"translate English to French: nlp is a field of artificial intelligence",
args=top_p_sampling_settings)
print(result) # nlp est un domaine de l’intelligence artificielle. n
print(result.text) # nlp est un domaine de l’intelligence artificielle. n
def test_tt_save():
happy_tt = HappyTextToText()
happy_tt.save("model/")
result_before = happy_tt.generate_text(
"translate English to French: Hello my name is Eric")
happy = HappyTextToText(load_path="model/")
result_after = happy.generate_text(
"translate English to French: Hello my name is Eric")
assert result_before.text == result_after.text
def example_7_2():
happy_tt = HappyTextToText("T5", "t5-small")
greedy_settings = TTSettings(no_repeat_ngram_size=2, max_length=20)
output_greedy = happy_tt.generate_text(
"translate English to French: nlp is a field of artificial intelligence ",
args=greedy_settings)
beam_settings = TTSettings(num_beams=5, max_length=20)
output_beam_search = happy_tt.generate_text(
"translate English to French: nlp is a field of artificial intelligence ",
args=beam_settings)
generic_sampling_settings = TTSettings(do_sample=True,
top_k=0,
temperature=0.7,
max_length=20)
output_generic_sampling = happy_tt.generate_text(
"translate English to French: nlp is a field of artificial intelligence ",
args=generic_sampling_settings)
top_k_sampling_settings = TTSettings(do_sample=True,
top_k=50,
temperature=0.7,
max_length=20)
output_top_k_sampling = happy_tt.generate_text(
"translate English to French: nlp is a field of artificial intelligence ",
args=top_k_sampling_settings)
top_p_sampling_settings = TTSettings(do_sample=True,
top_k=0,
top_p=0.8,
temperature=0.7,
max_length=20)
output_top_p_sampling = happy_tt.generate_text(
"translate English to French: nlp is a field of artificial intelligence ",
args=top_p_sampling_settings)
print("Greedy:", output_greedy.text
) # Greedy: nlp est un domaine de l'intelligence artificielle
print("Beam:", output_beam_search.text
) # Beam: nlp est un domaine de l'intelligence artificielle
print("Generic Sampling:", output_generic_sampling.text
) # Generic Sampling: nlp est un champ d'intelligence artificielle
print(
"Top-k Sampling:", output_top_k_sampling.text
) # Top-k Sampling: nlp est un domaine de l’intelligence artificielle
print(
"Top-p Sampling:", output_top_p_sampling.text
) # Top-p Sampling: nlp est un domaine de l'intelligence artificielle
def example_7_0():
# --------------------------------------#
happy_tt = HappyTextToText("T5", "t5-small") # default
def test_default_simple():
happy_tt = HappyTextToText()
output = happy_tt.generate_text(
"translate English to French: Hello my name is Eric")
assert type(output.text) == str
def test_all_methods():
happy_tt = HappyTextToText()
greedy_settings = TTSettings(min_length=5,
max_length=5,
no_repeat_ngram_size=2)
output_greedy = happy_tt.generate_text(
"translate English to French: Hello my name is Eric",
args=greedy_settings)
beam_settings = TTSettings(min_length=5,
max_length=5,
early_stopping=True,
num_beams=5)
output_beam_search = happy_tt.generate_text(
"translate English to French: Hello my name is Eric",
args=beam_settings)
generic_sampling_settings = TTSettings(min_length=5,
max_length=5,
do_sample=True,
early_stopping=False,
top_k=0,
temperature=0.7)
output_generic_sampling = happy_tt.generate_text(
"translate English to French: Hello my name is Eric",
args=generic_sampling_settings)
top_k_sampling_settings = TTSettings(min_length=5,
max_length=5,
do_sample=True,
early_stopping=False,
top_k=50,
temperature=0.7)
output_top_k_sampling = happy_tt.generate_text(
"translate English to French: Hello my name is Eric",
args=top_k_sampling_settings)
top_p_sampling_settings = TTSettings(min_length=5,
max_length=5,
do_sample=True,
early_stopping=False,
top_k=0,
top_p=0.8,
temperature=0.7)
output_top_p_sampling = happy_tt.generate_text(
"translate English to French: Hello my name is Eric",
args=top_p_sampling_settings)
assert type(output_greedy.text) == str
assert type(output_beam_search.text) == str
assert type(output_generic_sampling.text) == str
assert type(output_top_k_sampling.text) == str
assert type(output_top_p_sampling.text) == str
print("greedy: ", output_greedy.text, end="\n\n")
print("beam-search: ", output_beam_search.text, end="\n\n")
print("generic-sampling: ", output_generic_sampling.text, end="\n\n")
print("top-k-sampling: ", output_top_k_sampling.text, end="\n\n")
print("top-p-sampling: ", output_top_p_sampling.text, end="\n\n")