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[DOCS] Updating samples in GenAI Guide - port from 2024.6 (openvinoto…
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…olkit#28101)

Porting: 28100

Signed-off-by: sgolebiewski-intel <[email protected]>
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sgolebiewski-intel authored Dec 17, 2024
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104 changes: 48 additions & 56 deletions docs/articles_en/learn-openvino/llm_inference_guide/genai-guide.rst
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Expand Up @@ -39,100 +39,89 @@ make sure to :doc:`install OpenVINO with GenAI <../../get-started/install-openvi

.. tab-set::

.. tab-item:: main.py
:name: mainpy
.. tab-item:: text2image.py
:name: text2image

.. code-block:: python
import argparse
import openvino_genai
from PIL import Image
import numpy as np
class Generator(openvino_genai.Generator):
def __init__(self, seed, mu=0.0, sigma=1.0):
openvino_genai.Generator.__init__(self)
np.random.seed(seed)
self.mu = mu
self.sigma = sigma
def next(self):
return np.random.normal(self.mu, self.sigma)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('model_dir')
parser.add_argument('prompt')
args = parser.parse_args()
def infer(model_dir: str, prompt: str):
device = 'CPU' # GPU can be used as well
random_generator = Generator(42)
pipe = openvino_genai.Text2ImagePipeline(model_dir, device)
pipe = openvino_genai.Text2ImagePipeline(args.model_dir, device)
image_tensor = pipe.generate(
prompt,
args.prompt,
width=512,
height=512,
num_inference_steps=20,
num_images_per_prompt=1,
random_generator=random_generator
)
num_images_per_prompt=1)
image = Image.fromarray(image_tensor.data[0])
image.save("image.bmp")
.. tab-item:: LoRA.py
:name: lorapy
.. tab-item:: lora_text2image.py
:name: loratext2imagepy

.. code-block:: python
import openvino as ov
import openvino_genai
import numpy as np
import sys
class Generator(openvino_genai.Generator):
def __init__(self, seed, mu=0.0, sigma=1.0):
openvino_genai.Generator.__init__(self)
np.random.seed(seed)
self.mu = mu
self.sigma = sigma
def next(self):
return np.random.normal(self.mu, self.sigma)
def image_write(path: str, image_tensor: ov.Tensor):
from PIL import Image
image = Image.fromarray(image_tensor.data[0])
image.save(path)
def infer(models_path: str, prompt: str):
prompt = "cyberpunk cityscape like Tokyo New York with tall buildings at dusk golden hour cinematic lighting"
def main():
parser = argparse.ArgumentParser()
parser.add_argument('models_path')
parser.add_argument('prompt')
args, adapters = parser.parse_known_args()
prompt = args.prompt
device = "CPU" # GPU, NPU can be used as well
adapter_config = openvino_genai.AdapterConfig()
# Multiple LoRA adapters applied simultaneously are supported, parse them all and corresponding alphas from cmd parameters:
for i in range(int(len(adapters) / 2)):
adapter = openvino_genai.Adapter(adapters[2 * i])
alpha = float(adapters[2 * i + 1])
adapter_config.add(adapter, alpha)
pipe = openvino_genai.Text2ImagePipeline(models_path, device, adapters=adapter_config)
# LoRA adapters passed to the constructor will be activated by default in next generates
pipe = openvino_genai.Text2ImagePipeline(args.models_path, device, adapters=adapter_config)
print("Generating image with LoRA adapters applied, resulting image will be in lora.bmp")
image = pipe.generate(prompt,
random_generator=Generator(42),
width=512,
height=896,
num_inference_steps=20)
num_inference_steps=20,
rng_seed=42)
image_write("lora.bmp", image)
print("Generating image without LoRA adapters applied, resulting image will be in baseline.bmp")
image = pipe.generate(prompt,
# passing adapters in generate overrides adapters set in the constructor; openvino_genai.AdapterConfig() means no adapters
adapters=openvino_genai.AdapterConfig(),
random_generator=Generator(42),
width=512,
height=896,
num_inference_steps=20
)
num_inference_steps=20,
rng_seed=42)
image_write("baseline.bmp", image)
For more information, refer to the
`Python sample <https://github.com/openvinotoolkit/openvino.genai/tree/master/samples/python/image_generation>`__

Expand All @@ -141,20 +130,20 @@ make sure to :doc:`install OpenVINO with GenAI <../../get-started/install-openvi

.. tab-set::

.. tab-item:: main.cpp
:name: maincpp
.. tab-item:: text2image.cpp
:name: text2imagecpp

.. code-block:: cpp
#include "openvino/genai/text2image/pipeline.hpp"
#include "openvino/genai/image_generation/text2image_pipeline.hpp"
#include "imwrite.hpp"
int32_t main(int32_t argc, char* argv[]) try {
OPENVINO_ASSERT(argc == 3, "Usage: ", argv[0], " <MODEL_DIR> '<PROMPT>'");
const std::string models_path = argv[1], prompt = argv[2];
const std::string device = "CPU"; // GPU, NPU can be used as well
const std::string device = "CPU"; // GPU can be used as well
ov::genai::Text2ImagePipeline pipe(models_path, device);
ov::Tensor image = pipe.generate(prompt,
Expand All @@ -163,6 +152,7 @@ make sure to :doc:`install OpenVINO with GenAI <../../get-started/install-openvi
ov::genai::num_inference_steps(20),
ov::genai::num_images_per_prompt(1));
// writes `num_images_per_prompt` images by pattern name
imwrite("image_%d.bmp", image, true);
return EXIT_SUCCESS;
Expand All @@ -178,12 +168,12 @@ make sure to :doc:`install OpenVINO with GenAI <../../get-started/install-openvi
return EXIT_FAILURE;
}
.. tab-item:: LoRA.cpp
:name: loracpp
.. tab-item:: lora_text2image.cpp
:name: loratext2imagecpp

.. code-block:: cpp
#include "openvino/genai/text2image/pipeline.hpp"
#include "openvino/genai/image_generation/text2image_pipeline.hpp"
#include "imwrite.hpp"
Expand All @@ -194,29 +184,31 @@ make sure to :doc:`install OpenVINO with GenAI <../../get-started/install-openvi
const std::string device = "CPU"; // GPU, NPU can be used as well
ov::genai::AdapterConfig adapter_config;
// Multiple LoRA adapters applied simultaneously are supported, parse them all and corresponding alphas from cmd parameters:
for(size_t i = 0; i < (argc - 3)/2; ++i) {
ov::genai::Adapter adapter(argv[3 + 2*i]);
float alpha = std::atof(argv[3 + 2*i + 1]);
adapter_config.add(adapter, alpha);
}
// LoRA adapters passed to the constructor will be activated by default in next generates
ov::genai::Text2ImagePipeline pipe(models_path, device, ov::genai::adapters(adapter_config));
std::cout << "Generating image with LoRA adapters applied, resulting image will be in lora.bmp\n";
ov::Tensor image = pipe.generate(prompt,
ov::genai::random_generator(std::make_shared<ov::genai::CppStdGenerator>(42)),
ov::genai::width(512),
ov::genai::height(896),
ov::genai::num_inference_steps(20));
ov::genai::num_inference_steps(20),
ov::genai::rng_seed(42));
imwrite("lora.bmp", image, true);
std::cout << "Generating image without LoRA adapters applied, resulting image will be in baseline.bmp\n";
image = pipe.generate(prompt,
ov::genai::adapters(),
ov::genai::random_generator(std::make_shared<ov::genai::CppStdGenerator>(42)),
ov::genai::adapters(), // passing adapters in generate overrides adapters set in the constructor; adapters() means no adapters
ov::genai::width(512),
ov::genai::height(896),
ov::genai::num_inference_steps(20));
ov::genai::num_inference_steps(20),
ov::genai::rng_seed(42));
imwrite("baseline.bmp", image, true);
return EXIT_SUCCESS;
Expand All @@ -233,7 +225,7 @@ make sure to :doc:`install OpenVINO with GenAI <../../get-started/install-openvi
}
For more information, refer to the
`C++ sample <https://github.com/openvinotoolkit/openvino.genai/tree/master/samples/cpp/text2image/>`__
`C++ sample <https://github.com/openvinotoolkit/openvino.genai/tree/master/samples/cpp/image_generation/>`__


.. dropdown:: Speech Recognition
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