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inference_cpu.py

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+import os
+import numpy as np
+import onnx
+import onnxruntime as ort
+
+
+# The directory of your input and output data
+input_data_dir = 'input_data'
+output_data_dir = 'output_data'
+model_24 = onnx.load('pangu_weather_24.onnx')
+
+# Set the behavier of onnxruntime
+options = ort.SessionOptions()
+options.enable_cpu_mem_arena=False
+options.enable_mem_pattern = False
+options.enable_mem_reuse = False
+# Increase the number for faster inference and more memory consumption
+options.intra_op_num_threads = 1
+
+# Set the behavier of cuda provider
+cuda_provider_options = {'arena_extend_strategy':'kSameAsRequested',}
+
+# Initialize onnxruntime session for Pangu-Weather Models
+ort_session_24 = ort.InferenceSession('pangu_weather_24.onnx', sess_options=options, provider=['CPUExecutionProvider'])
+
+# Load the upper-air numpy arrays
+input = np.load(os.path.join(input_data_dir, 'input_upper.npy')).astype(np.float32)
+# Load the surface numpy arrays
+input_surface = np.load(os.path.join(input_data_dir, 'input_surface.npy')).astype(np.float32)
+
+# Run the inference session
+output, output_surface = ort_session_24.run(None, {'input':input, 'input_surface':input_surface})
+
+# Save the results
+np.save(os.path.join(output_data_dir, 'output_upper'), output)
+np.save(os.path.join(output_data_dir, 'output_surface'), output_surface)

inference_gpu.py

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+import os
+import numpy as np
+import onnx
+import onnxruntime as ort
+
+
+# The directory of your input and output data
+input_data_dir = 'input_data'
+output_data_dir = 'output_data'
+model_24 = onnx.load('pangu_weather_24.onnx')
+
+# Set the behavier of onnxruntime
+options = ort.SessionOptions()
+options.enable_cpu_mem_arena=False
+options.enable_mem_pattern = False
+options.enable_mem_reuse = False
+# Increase the number for faster inference and more memory consumption
+options.intra_op_num_threads = 1
+
+# Set the behavier of cuda provider
+cuda_provider_options = {'arena_extend_strategy':'kSameAsRequested',}
+
+# Initialize onnxruntime session for Pangu-Weather Models
+ort_session_24 = ort.InferenceSession('pangu_weather_24.onnx', sess_options=options, provider=[('CUDAExecutionProvider', cuda_provider_options)])
+
+# Load the upper-air numpy arrays
+input = np.load(os.path.join(input_data_dir, 'input_upper.npy')).astype(np.float32)
+# Load the surface numpy arrays
+input_surface = np.load(os.path.join(input_data_dir, 'input_surface.npy')).astype(np.float32)
+
+# Run the inference session
+output, output_surface = ort_session_24.run(None, {'input':input, 'input_surface':input_surface})
+# Save the results
+np.save(os.path.join(output_data_dir, 'output_upper'), output)
+np.save(os.path.join(output_data_dir, 'output_surface'), output_surface)

inference_iterative.py

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+import os
+import numpy as np
+import onnx
+import onnxruntime as ort
+
+
+# The directory of your input and output data
+input_data_dir = 'input_data'
+output_data_dir = 'output_data'
+model_24 = onnx.load('pangu_weather_24.onnx')
+model_6 = onnx.load('pangu_weather_6.onnx')
+
+# Set the behavier of onnxruntime
+options = ort.SessionOptions()
+options.enable_cpu_mem_arena=False
+options.enable_mem_pattern = False
+options.enable_mem_reuse = False
+# Increase the number for faster inference and more memory consumption
+options.intra_op_num_threads = 1
+
+# Set the behavier of cuda provider
+cuda_provider_options = {'arena_extend_strategy':'kSameAsRequested',}
+
+# Initialize onnxruntime session for Pangu-Weather Models
+ort_session_24 = ort.InferenceSession('pangu_weather_24.onnx', sess_options=options, provider=[('CUDAExecutionProvider', cuda_provider_options)])
+ort_session_6 = ort.InferenceSession('pangu_weather_6.onnx', sess_options=options, provider=[('CUDAExecutionProvider', cuda_provider_options)])
+
+# Load the upper-air numpy arrays
+input = np.load(os.path.join(input_data_dir, 'input_upper.npy')).astype(np.float32)
+# Load the surface numpy arrays
+input_surface = np.load(os.path.join(input_data_dir, 'input_surface.npy')).astype(np.float32)
+
+# Run the inference session
+input_24, input_surface_24 = input, input_surface
+for i in range(28):
+  if (i+1) % 4 == 0:
+    output, output_surface = ort_session_24.run(None, {'input':input_24, 'input_surface':input_surface_24})
+    input_24, input_surface_24 = output, output_surface
+  else:
+    output, output_surface = ort_session_6.run(None, {'input':input, 'input_surface':input_surface})
+  input, input_surface = output, output_surface
+  # Your can save the results here