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Use CUDA to generate images faster (#1)
Browse files- Use CUDA to generate images faster (557e09045478b9d700094b3b07ea3a71f02269bf)
Co-authored-by: Muhammad Nabeel Raza <nabeelraza@users.noreply.huggingface.co>
- inference_code.py +5 -2
inference_code.py
CHANGED
@@ -5,13 +5,16 @@ from flax.training.common_utils import shard
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from diffusers import FlaxStableDiffusionPipeline
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model_path = "sabman/map-diffuser-v3"
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pipeline, _params = FlaxStableDiffusionPipeline.from_pretrained(model_path, dtype=jax.numpy.bfloat16)
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# prompt = "create a map with traffic signals, busway and residential buildings, in water color style"
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def generate_images(prompt):
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prng_seed = jax.random.PRNGKey(-1)
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num_inference_steps =
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num_samples = jax.device_count()
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prompt = num_samples * [prompt]
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from diffusers import FlaxStableDiffusionPipeline
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model_path = "sabman/map-diffuser-v3"
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# pipeline, _params = FlaxStableDiffusionPipeline.from_pretrained(model_path, dtype=jax.numpy.bfloat16)
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pipeline = DiffusionPipeline.from_pretrained(
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model_path,
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from_flax=True, safety_checker=None).to("cuda")
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# prompt = "create a map with traffic signals, busway and residential buildings, in water color style"
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def generate_images(prompt):
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prng_seed = jax.random.PRNGKey(-1)
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num_inference_steps = 20
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num_samples = jax.device_count()
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prompt = num_samples * [prompt]
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