mirror of
https://github.com/azaion/detections.git
synced 2026-04-23 03:36:32 +00:00
Refactor inference and AI configuration handling
- Updated the `Inference` class to replace the `get_onnx_engine_bytes` method with `download_model`, allowing for dynamic model loading based on a specified filename. - Modified the `convert_and_upload_model` method to accept `source_bytes` instead of `onnx_engine_bytes`, enhancing flexibility in model conversion. - Introduced a new property `engine_name` to the `Inference` class for better access to engine details. - Adjusted the `AIRecognitionConfig` structure to include a new method pointer `from_dict`, improving configuration handling. - Updated various test cases to reflect changes in model paths and timeout settings, ensuring consistency and reliability in testing.
This commit is contained in:
Oleksandr Bezdieniezhnykh
+1705
-4030
File diff suppressed because it is too large
Load Diff
@@ -4,9 +4,8 @@ from engines.inference_engine cimport InferenceEngine
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cdef class CoreMLEngine(InferenceEngine):
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cdef object model
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cdef str input_name
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cdef tuple input_shape
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cdef list _output_names
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cdef int img_width
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cdef int img_height
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cdef tuple get_input_shape(self)
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cdef int get_batch_size(self)
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+39
-53
@@ -1,6 +1,7 @@
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from engines.inference_engine cimport InferenceEngine
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cimport constants_inf
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import numpy as np
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from PIL import Image
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import io
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import os
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import tempfile
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@@ -21,18 +22,12 @@ cdef class CoreMLEngine(InferenceEngine):
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model_path, compute_units=ct.ComputeUnit.ALL)
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spec = self.model.get_spec()
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input_desc = spec.description.input[0]
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self.input_name = input_desc.name
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img_input = spec.description.input[0]
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self.img_width = int(img_input.type.imageType.width)
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self.img_height = int(img_input.type.imageType.height)
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self.batch_size = 1
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array_type = input_desc.type.multiArrayType
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self.input_shape = tuple(int(s) for s in array_type.shape)
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if len(self.input_shape) == 4:
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self.batch_size = self.input_shape[0] if self.input_shape[0] > 0 else batch_size
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self._output_names = [o.name for o in spec.description.output]
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constants_inf.log(<str>f'CoreML model: input={self.input_name} shape={self.input_shape}')
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constants_inf.log(<str>f'CoreML outputs: {self._output_names}')
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constants_inf.log(<str>f'CoreML model: {self.img_width}x{self.img_height}')
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@property
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def engine_name(self):
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@@ -42,38 +37,6 @@ cdef class CoreMLEngine(InferenceEngine):
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def get_engine_filename():
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return "azaion_coreml.zip"
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@staticmethod
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def convert_from_onnx(bytes onnx_bytes):
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import coremltools as ct
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with tempfile.NamedTemporaryFile(suffix='.onnx', delete=False) as f:
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f.write(onnx_bytes)
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onnx_path = f.name
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try:
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constants_inf.log(<str>'Converting ONNX to CoreML...')
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model = ct.convert(
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onnx_path,
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compute_units=ct.ComputeUnit.ALL,
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minimum_deployment_target=ct.target.macOS13,
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)
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with tempfile.TemporaryDirectory() as tmpdir:
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pkg_path = os.path.join(tmpdir, "azaion.mlpackage")
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model.save(pkg_path)
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buf = io.BytesIO()
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with zipfile.ZipFile(buf, 'w', zipfile.ZIP_DEFLATED) as zf:
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for root, dirs, files in os.walk(pkg_path):
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for fname in files:
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file_path = os.path.join(root, fname)
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arcname = os.path.relpath(file_path, tmpdir)
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zf.write(file_path, arcname)
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constants_inf.log(<str>'CoreML conversion done!')
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return buf.getvalue()
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finally:
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os.unlink(onnx_path)
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@staticmethod
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def _extract_from_zip(model_bytes):
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tmpdir = tempfile.mkdtemp()
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@@ -86,17 +49,40 @@ cdef class CoreMLEngine(InferenceEngine):
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raise ValueError("No .mlpackage or .mlmodel found in zip")
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cdef tuple get_input_shape(self):
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return self.input_shape[2], self.input_shape[3]
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return self.img_height, self.img_width
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cdef int get_batch_size(self):
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return self.batch_size
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return 1
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cdef run(self, input_data):
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prediction = self.model.predict({self.input_name: input_data})
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results = []
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for name in self._output_names:
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val = prediction[name]
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if not isinstance(val, np.ndarray):
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val = np.array(val)
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results.append(val)
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return results
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cdef int w = self.img_width
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cdef int h = self.img_height
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blob = input_data[0]
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img_array = np.clip(blob * 255.0, 0, 255).astype(np.uint8)
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img_array = np.transpose(img_array, (1, 2, 0))
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pil_img = Image.fromarray(img_array, 'RGB')
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pred = self.model.predict({
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'image': pil_img,
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'iouThreshold': 0.45,
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'confidenceThreshold': 0.25,
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})
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coords = pred.get('coordinates', np.empty((0, 4), dtype=np.float32))
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confs = pred.get('confidence', np.empty((0, 80), dtype=np.float32))
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if coords.size == 0:
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return [np.zeros((1, 0, 6), dtype=np.float32)]
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cx, cy, bw, bh = coords[:, 0], coords[:, 1], coords[:, 2], coords[:, 3]
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x1 = (cx - bw / 2) * w
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y1 = (cy - bh / 2) * h
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x2 = (cx + bw / 2) * w
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y2 = (cy + bh / 2) * h
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class_ids = np.argmax(confs, axis=1).astype(np.float32)
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conf_values = np.max(confs, axis=1)
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dets = np.stack([x1, y1, x2, y2, conf_values, class_ids], axis=1)
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return [dets[np.newaxis, :, :]]
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+216
-121
@@ -4,7 +4,7 @@
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{
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"distutils": {
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"include_dirs": [
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"/Users/obezdienie001/dev/azaion/suite/detections/.venv/lib/python3.13/site-packages/numpy/_core/include"
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"/Users/obezdienie001/dev/azaion/suite/detections/.venv-e2e/lib/python3.13/site-packages/numpy/_core/include"
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],
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"name": "engines.inference_engine",
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"sources": [
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@@ -2310,13 +2310,13 @@ static const char __pyx_k_isenabled[] = "isenabled";
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static const char __pyx_k_pyx_state[] = "__pyx_state";
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static const char __pyx_k_reduce_ex[] = "__reduce_ex__";
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static const char __pyx_k_batch_size[] = "batch_size";
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static const char __pyx_k_onnx_bytes[] = "onnx_bytes";
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static const char __pyx_k_pyx_result[] = "__pyx_result";
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static const char __pyx_k_pyx_vtable[] = "__pyx_vtable__";
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static const char __pyx_k_PickleError[] = "PickleError";
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static const char __pyx_k_model_bytes[] = "model_bytes";
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static const char __pyx_k_is_coroutine[] = "_is_coroutine";
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static const char __pyx_k_pyx_checksum[] = "__pyx_checksum";
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static const char __pyx_k_source_bytes[] = "source_bytes";
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static const char __pyx_k_staticmethod[] = "staticmethod";
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static const char __pyx_k_stringsource[] = "<stringsource>";
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static const char __pyx_k_use_setstate[] = "use_setstate";
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@@ -2324,11 +2324,12 @@ static const char __pyx_k_reduce_cython[] = "__reduce_cython__";
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static const char __pyx_k_InferenceEngine[] = "InferenceEngine";
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static const char __pyx_k_pyx_PickleError[] = "__pyx_PickleError";
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static const char __pyx_k_setstate_cython[] = "__setstate_cython__";
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static const char __pyx_k_convert_from_onnx[] = "convert_from_onnx";
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static const char __pyx_k_asyncio_coroutines[] = "asyncio.coroutines";
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static const char __pyx_k_cline_in_traceback[] = "cline_in_traceback";
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static const char __pyx_k_NotImplementedError[] = "NotImplementedError";
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static const char __pyx_k_convert_from_source[] = "convert_from_source";
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static const char __pyx_k_get_engine_filename[] = "get_engine_filename";
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static const char __pyx_k_get_source_filename[] = "get_source_filename";
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static const char __pyx_k_engines_inference_engine[] = "engines.inference_engine";
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static const char __pyx_k_hk_A_1_uuwwx_1_7_1_2DNRS_1[] = "\200\001\360\006\000\005\010\200\177\220h\230k\250\033\260A\330\010\r\210^\2301\330\010\016\320\016!\320!u\320uw\320wx\330\004\023\220?\240(\250!\2501\330\004\007\200|\2207\230!\330\0101\260\021\3202D\300N\320RS\330\004\013\2101";
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static const char __pyx_k_Subclass_must_implement_run[] = "Subclass must implement run";
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@@ -2338,19 +2339,21 @@ static const char __pyx_k_InferenceEngine___reduce_cython[] = "InferenceEngine._
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static const char __pyx_k_T_G1F_a_vWA_q_q_q_0_AWKwa_0_AWK[] = "\200\001\360\010\000\005\016\210T\220\021\330\004\014\210G\2201\220F\230,\240a\330\004\007\200v\210W\220A\330\010\022\220!\330\010\027\220q\340\010\027\220q\330\004\007\200q\330\010\017\320\0170\260\004\260A\260W\270K\300w\310a\340\010\017\320\0170\260\004\260A\260W\270K\300q";
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static const char __pyx_k_Incompatible_checksums_0x_x_vs_0[] = "Incompatible checksums (0x%x vs (0x37a72fb, 0x763015b, 0xe11ccd4) = (batch_size))";
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static const char __pyx_k_InferenceEngine___setstate_cytho[] = "InferenceEngine.__setstate_cython__";
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static const char __pyx_k_InferenceEngine_convert_from_onn[] = "InferenceEngine.convert_from_onnx";
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static const char __pyx_k_InferenceEngine_convert_from_sou[] = "InferenceEngine.convert_from_source";
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static const char __pyx_k_InferenceEngine_get_engine_filen[] = "InferenceEngine.get_engine_filename";
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static const char __pyx_k_InferenceEngine_get_source_filen[] = "InferenceEngine.get_source_filename";
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static const char __pyx_k_Note_that_Cython_is_deliberately[] = "Note that Cython is deliberately stricter than PEP-484 and rejects subclasses of builtin types. If you need to pass subclasses then set the 'annotation_typing' directive to False.";
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static const char __pyx_k_Subclass_must_implement_get_inpu[] = "Subclass must implement get_input_shape";
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/* #### Code section: decls ### */
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static int __pyx_pf_7engines_16inference_engine_15InferenceEngine___init__(struct __pyx_obj_7engines_16inference_engine_InferenceEngine *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_model_bytes, PyObject *__pyx_v_batch_size, CYTHON_UNUSED PyObject *__pyx_v_kwargs); /* proto */
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static PyObject *__pyx_pf_7engines_16inference_engine_15InferenceEngine_11engine_name___get__(CYTHON_UNUSED struct __pyx_obj_7engines_16inference_engine_InferenceEngine *__pyx_v_self); /* proto */
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static PyObject *__pyx_pf_7engines_16inference_engine_15InferenceEngine_2get_engine_filename(void); /* proto */
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static PyObject *__pyx_pf_7engines_16inference_engine_15InferenceEngine_4convert_from_onnx(PyObject *__pyx_v_onnx_bytes); /* proto */
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static PyObject *__pyx_pf_7engines_16inference_engine_15InferenceEngine_4get_source_filename(void); /* proto */
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static PyObject *__pyx_pf_7engines_16inference_engine_15InferenceEngine_6convert_from_source(PyObject *__pyx_v_source_bytes); /* proto */
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static PyObject *__pyx_pf_7engines_16inference_engine_15InferenceEngine_10batch_size___get__(struct __pyx_obj_7engines_16inference_engine_InferenceEngine *__pyx_v_self); /* proto */
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static int __pyx_pf_7engines_16inference_engine_15InferenceEngine_10batch_size_2__set__(struct __pyx_obj_7engines_16inference_engine_InferenceEngine *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
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static PyObject *__pyx_pf_7engines_16inference_engine_15InferenceEngine_6__reduce_cython__(struct __pyx_obj_7engines_16inference_engine_InferenceEngine *__pyx_v_self); /* proto */
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static PyObject *__pyx_pf_7engines_16inference_engine_15InferenceEngine_8__setstate_cython__(struct __pyx_obj_7engines_16inference_engine_InferenceEngine *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
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static PyObject *__pyx_pf_7engines_16inference_engine_15InferenceEngine_8__reduce_cython__(struct __pyx_obj_7engines_16inference_engine_InferenceEngine *__pyx_v_self); /* proto */
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static PyObject *__pyx_pf_7engines_16inference_engine_15InferenceEngine_10__setstate_cython__(struct __pyx_obj_7engines_16inference_engine_InferenceEngine *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
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static PyObject *__pyx_pf_7engines_16inference_engine___pyx_unpickle_InferenceEngine(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
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static PyObject *__pyx_tp_new_7engines_16inference_engine_InferenceEngine(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
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/* #### Code section: late_includes ### */
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@@ -2395,8 +2398,8 @@ typedef struct {
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PyTypeObject *__pyx_ptype_7engines_16inference_engine_InferenceEngine;
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__Pyx_CachedCFunction __pyx_umethod_PyDict_Type_pop;
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PyObject *__pyx_tuple[1];
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PyObject *__pyx_codeobj_tab[5];
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PyObject *__pyx_string_tab[60];
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PyObject *__pyx_codeobj_tab[6];
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PyObject *__pyx_string_tab[62];
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PyObject *__pyx_int_1;
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PyObject *__pyx_int_58356475;
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PyObject *__pyx_int_123928923;
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@@ -2443,61 +2446,63 @@ static __pyx_mstatetype * const __pyx_mstate_global = &__pyx_mstate_global_stati
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#define __pyx_n_u_InferenceEngine __pyx_string_tab[2]
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#define __pyx_n_u_InferenceEngine___reduce_cython __pyx_string_tab[3]
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#define __pyx_n_u_InferenceEngine___setstate_cytho __pyx_string_tab[4]
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#define __pyx_n_u_InferenceEngine_convert_from_onn __pyx_string_tab[5]
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#define __pyx_n_u_InferenceEngine_convert_from_sou __pyx_string_tab[5]
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#define __pyx_n_u_InferenceEngine_get_engine_filen __pyx_string_tab[6]
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#define __pyx_n_u_NotImplementedError __pyx_string_tab[7]
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#define __pyx_kp_u_Note_that_Cython_is_deliberately __pyx_string_tab[8]
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#define __pyx_n_u_PickleError __pyx_string_tab[9]
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#define __pyx_kp_u_Subclass_must_implement_get_inpu __pyx_string_tab[10]
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#define __pyx_kp_u_Subclass_must_implement_run __pyx_string_tab[11]
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#define __pyx_kp_u__2 __pyx_string_tab[12]
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#define __pyx_kp_u_add_note __pyx_string_tab[13]
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#define __pyx_n_u_asyncio_coroutines __pyx_string_tab[14]
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#define __pyx_n_u_batch_size __pyx_string_tab[15]
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#define __pyx_n_u_cline_in_traceback __pyx_string_tab[16]
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#define __pyx_n_u_convert_from_onnx __pyx_string_tab[17]
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#define __pyx_n_u_dict __pyx_string_tab[18]
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#define __pyx_n_u_dict_2 __pyx_string_tab[19]
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#define __pyx_kp_u_disable __pyx_string_tab[20]
|
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#define __pyx_kp_u_enable __pyx_string_tab[21]
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#define __pyx_n_u_engines_inference_engine __pyx_string_tab[22]
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#define __pyx_kp_u_engines_inference_engine_pyx __pyx_string_tab[23]
|
||||
#define __pyx_n_u_func __pyx_string_tab[24]
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||||
#define __pyx_kp_u_gc __pyx_string_tab[25]
|
||||
#define __pyx_n_u_get_engine_filename __pyx_string_tab[26]
|
||||
#define __pyx_n_u_getstate __pyx_string_tab[27]
|
||||
#define __pyx_n_u_is_coroutine __pyx_string_tab[28]
|
||||
#define __pyx_kp_u_isenabled __pyx_string_tab[29]
|
||||
#define __pyx_n_u_main __pyx_string_tab[30]
|
||||
#define __pyx_n_u_model_bytes __pyx_string_tab[31]
|
||||
#define __pyx_n_u_module __pyx_string_tab[32]
|
||||
#define __pyx_n_u_name __pyx_string_tab[33]
|
||||
#define __pyx_n_u_new __pyx_string_tab[34]
|
||||
#define __pyx_n_u_onnx __pyx_string_tab[35]
|
||||
#define __pyx_n_u_onnx_bytes __pyx_string_tab[36]
|
||||
#define __pyx_n_u_pickle __pyx_string_tab[37]
|
||||
#define __pyx_n_u_pop __pyx_string_tab[38]
|
||||
#define __pyx_n_u_pyx_PickleError __pyx_string_tab[39]
|
||||
#define __pyx_n_u_pyx_checksum __pyx_string_tab[40]
|
||||
#define __pyx_n_u_pyx_result __pyx_string_tab[41]
|
||||
#define __pyx_n_u_pyx_state __pyx_string_tab[42]
|
||||
#define __pyx_n_u_pyx_type __pyx_string_tab[43]
|
||||
#define __pyx_n_u_pyx_unpickle_InferenceEngine __pyx_string_tab[44]
|
||||
#define __pyx_n_u_pyx_vtable __pyx_string_tab[45]
|
||||
#define __pyx_n_u_qualname __pyx_string_tab[46]
|
||||
#define __pyx_n_u_reduce __pyx_string_tab[47]
|
||||
#define __pyx_n_u_reduce_cython __pyx_string_tab[48]
|
||||
#define __pyx_n_u_reduce_ex __pyx_string_tab[49]
|
||||
#define __pyx_n_u_self __pyx_string_tab[50]
|
||||
#define __pyx_n_u_set_name __pyx_string_tab[51]
|
||||
#define __pyx_n_u_setstate __pyx_string_tab[52]
|
||||
#define __pyx_n_u_setstate_cython __pyx_string_tab[53]
|
||||
#define __pyx_n_u_state __pyx_string_tab[54]
|
||||
#define __pyx_n_u_staticmethod __pyx_string_tab[55]
|
||||
#define __pyx_kp_u_stringsource __pyx_string_tab[56]
|
||||
#define __pyx_n_u_test __pyx_string_tab[57]
|
||||
#define __pyx_n_u_update __pyx_string_tab[58]
|
||||
#define __pyx_n_u_use_setstate __pyx_string_tab[59]
|
||||
#define __pyx_n_u_InferenceEngine_get_source_filen __pyx_string_tab[7]
|
||||
#define __pyx_n_u_NotImplementedError __pyx_string_tab[8]
|
||||
#define __pyx_kp_u_Note_that_Cython_is_deliberately __pyx_string_tab[9]
|
||||
#define __pyx_n_u_PickleError __pyx_string_tab[10]
|
||||
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#define __pyx_kp_u_disable __pyx_string_tab[21]
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for (int i=0; i<62; ++i) { __Pyx_VISIT_CONST(traverse_module_state->__pyx_string_tab[i]); }
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__Pyx_VISIT_CONST(traverse_module_state->__pyx_int_1);
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__Pyx_VISIT_CONST(traverse_module_state->__pyx_int_58356475);
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__Pyx_VISIT_CONST(traverse_module_state->__pyx_int_123928923);
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@@ -2776,22 +2781,82 @@ static PyObject *__pyx_pf_7engines_16inference_engine_15InferenceEngine_2get_eng
|
||||
|
||||
|
||||
/* Python wrapper */
|
||||
static PyObject *__pyx_pw_7engines_16inference_engine_15InferenceEngine_5convert_from_onnx(CYTHON_UNUSED PyObject *__pyx_self,
|
||||
static PyObject *__pyx_pw_7engines_16inference_engine_15InferenceEngine_5get_source_filename(CYTHON_UNUSED PyObject *__pyx_self,
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#if CYTHON_METH_FASTCALL
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||||
PyObject *const *__pyx_args, Py_ssize_t __pyx_nargs, PyObject *__pyx_kwds
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PyObject *__pyx_args, PyObject *__pyx_kwds
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|
||||
); /*proto*/
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||||
static PyMethodDef __pyx_mdef_7engines_16inference_engine_15InferenceEngine_5convert_from_onnx = {"convert_from_onnx", (PyCFunction)(void(*)(void))(__Pyx_PyCFunction_FastCallWithKeywords)__pyx_pw_7engines_16inference_engine_15InferenceEngine_5convert_from_onnx, __Pyx_METH_FASTCALL|METH_KEYWORDS, 0};
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||||
static PyObject *__pyx_pw_7engines_16inference_engine_15InferenceEngine_5convert_from_onnx(CYTHON_UNUSED PyObject *__pyx_self,
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static PyMethodDef __pyx_mdef_7engines_16inference_engine_15InferenceEngine_5get_source_filename = {"get_source_filename", (PyCFunction)(void(*)(void))(__Pyx_PyCFunction_FastCallWithKeywords)__pyx_pw_7engines_16inference_engine_15InferenceEngine_5get_source_filename, __Pyx_METH_FASTCALL|METH_KEYWORDS, 0};
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PyObject *const *__pyx_args, Py_ssize_t __pyx_nargs, PyObject *__pyx_kwds
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static PyObject *__pyx_pw_7engines_16inference_engine_15InferenceEngine_7convert_from_source(CYTHON_UNUSED PyObject *__pyx_self,
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||||
#if CYTHON_METH_FASTCALL
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PyObject *const *__pyx_args, Py_ssize_t __pyx_nargs, PyObject *__pyx_kwds
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static PyMethodDef __pyx_mdef_7engines_16inference_engine_15InferenceEngine_7convert_from_source = {"convert_from_source", (PyCFunction)(void(*)(void))(__Pyx_PyCFunction_FastCallWithKeywords)__pyx_pw_7engines_16inference_engine_15InferenceEngine_7convert_from_source, __Pyx_METH_FASTCALL|METH_KEYWORDS, 0};
|
||||
static PyObject *__pyx_pw_7engines_16inference_engine_15InferenceEngine_7convert_from_source(CYTHON_UNUSED PyObject *__pyx_self,
|
||||
#if CYTHON_METH_FASTCALL
|
||||
PyObject *const *__pyx_args, Py_ssize_t __pyx_nargs, PyObject *__pyx_kwds
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||||
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PyObject *__pyx_args, PyObject *__pyx_kwds
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||||
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PyObject *__pyx_r = 0;
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||||
__pyx_nargs = PyTuple_GET_SIZE(__pyx_args);
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@@ -2812,46 +2877,46 @@ PyObject *__pyx_args, PyObject *__pyx_kwds
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||||
#endif
|
||||
__pyx_kwvalues = __Pyx_KwValues_FASTCALL(__pyx_args, __pyx_nargs);
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{
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||||
PyObject ** const __pyx_pyargnames[] = {&__pyx_mstate_global->__pyx_n_u_onnx_bytes,0};
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PyObject ** const __pyx_pyargnames[] = {&__pyx_mstate_global->__pyx_n_u_source_bytes,0};
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const Py_ssize_t __pyx_kwds_len = (__pyx_kwds) ? __Pyx_NumKwargs_FASTCALL(__pyx_kwds) : 0;
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CYTHON_FALLTHROUGH;
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if (__Pyx_ParseKeywords(__pyx_kwds, __pyx_kwvalues, __pyx_pyargnames, 0, values, kwd_pos_args, __pyx_kwds_len, "convert_from_onnx", 0) < 0) __PYX_ERR(0, 13, __pyx_L3_error)
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if (PyDict_SetItem(__pyx_mstate_global->__pyx_d, __pyx_mstate_global->__pyx_n_u_pyx_unpickle_InferenceEngine, __pyx_t_2) < 0) __PYX_ERR(2, 1, __pyx_L1_error)
|
||||
__Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
|
||||
@@ -4310,8 +4398,9 @@ static const __Pyx_StringTabEntry __pyx_string_tab[] = {
|
||||
{__pyx_k_InferenceEngine, sizeof(__pyx_k_InferenceEngine), 0, 1, 1}, /* PyObject cname: __pyx_n_u_InferenceEngine */
|
||||
{__pyx_k_InferenceEngine___reduce_cython, sizeof(__pyx_k_InferenceEngine___reduce_cython), 0, 1, 1}, /* PyObject cname: __pyx_n_u_InferenceEngine___reduce_cython */
|
||||
{__pyx_k_InferenceEngine___setstate_cytho, sizeof(__pyx_k_InferenceEngine___setstate_cytho), 0, 1, 1}, /* PyObject cname: __pyx_n_u_InferenceEngine___setstate_cytho */
|
||||
{__pyx_k_InferenceEngine_convert_from_onn, sizeof(__pyx_k_InferenceEngine_convert_from_onn), 0, 1, 1}, /* PyObject cname: __pyx_n_u_InferenceEngine_convert_from_onn */
|
||||
{__pyx_k_InferenceEngine_convert_from_sou, sizeof(__pyx_k_InferenceEngine_convert_from_sou), 0, 1, 1}, /* PyObject cname: __pyx_n_u_InferenceEngine_convert_from_sou */
|
||||
{__pyx_k_InferenceEngine_get_engine_filen, sizeof(__pyx_k_InferenceEngine_get_engine_filen), 0, 1, 1}, /* PyObject cname: __pyx_n_u_InferenceEngine_get_engine_filen */
|
||||
{__pyx_k_InferenceEngine_get_source_filen, sizeof(__pyx_k_InferenceEngine_get_source_filen), 0, 1, 1}, /* PyObject cname: __pyx_n_u_InferenceEngine_get_source_filen */
|
||||
{__pyx_k_NotImplementedError, sizeof(__pyx_k_NotImplementedError), 0, 1, 1}, /* PyObject cname: __pyx_n_u_NotImplementedError */
|
||||
{__pyx_k_Note_that_Cython_is_deliberately, sizeof(__pyx_k_Note_that_Cython_is_deliberately), 0, 1, 0}, /* PyObject cname: __pyx_kp_u_Note_that_Cython_is_deliberately */
|
||||
{__pyx_k_PickleError, sizeof(__pyx_k_PickleError), 0, 1, 1}, /* PyObject cname: __pyx_n_u_PickleError */
|
||||
@@ -4322,7 +4411,7 @@ static const __Pyx_StringTabEntry __pyx_string_tab[] = {
|
||||
{__pyx_k_asyncio_coroutines, sizeof(__pyx_k_asyncio_coroutines), 0, 1, 1}, /* PyObject cname: __pyx_n_u_asyncio_coroutines */
|
||||
{__pyx_k_batch_size, sizeof(__pyx_k_batch_size), 0, 1, 1}, /* PyObject cname: __pyx_n_u_batch_size */
|
||||
{__pyx_k_cline_in_traceback, sizeof(__pyx_k_cline_in_traceback), 0, 1, 1}, /* PyObject cname: __pyx_n_u_cline_in_traceback */
|
||||
{__pyx_k_convert_from_onnx, sizeof(__pyx_k_convert_from_onnx), 0, 1, 1}, /* PyObject cname: __pyx_n_u_convert_from_onnx */
|
||||
{__pyx_k_convert_from_source, sizeof(__pyx_k_convert_from_source), 0, 1, 1}, /* PyObject cname: __pyx_n_u_convert_from_source */
|
||||
{__pyx_k_dict, sizeof(__pyx_k_dict), 0, 1, 1}, /* PyObject cname: __pyx_n_u_dict */
|
||||
{__pyx_k_dict_2, sizeof(__pyx_k_dict_2), 0, 1, 1}, /* PyObject cname: __pyx_n_u_dict_2 */
|
||||
{__pyx_k_disable, sizeof(__pyx_k_disable), 0, 1, 0}, /* PyObject cname: __pyx_kp_u_disable */
|
||||
@@ -4332,6 +4421,7 @@ static const __Pyx_StringTabEntry __pyx_string_tab[] = {
|
||||
{__pyx_k_func, sizeof(__pyx_k_func), 0, 1, 1}, /* PyObject cname: __pyx_n_u_func */
|
||||
{__pyx_k_gc, sizeof(__pyx_k_gc), 0, 1, 0}, /* PyObject cname: __pyx_kp_u_gc */
|
||||
{__pyx_k_get_engine_filename, sizeof(__pyx_k_get_engine_filename), 0, 1, 1}, /* PyObject cname: __pyx_n_u_get_engine_filename */
|
||||
{__pyx_k_get_source_filename, sizeof(__pyx_k_get_source_filename), 0, 1, 1}, /* PyObject cname: __pyx_n_u_get_source_filename */
|
||||
{__pyx_k_getstate, sizeof(__pyx_k_getstate), 0, 1, 1}, /* PyObject cname: __pyx_n_u_getstate */
|
||||
{__pyx_k_is_coroutine, sizeof(__pyx_k_is_coroutine), 0, 1, 1}, /* PyObject cname: __pyx_n_u_is_coroutine */
|
||||
{__pyx_k_isenabled, sizeof(__pyx_k_isenabled), 0, 1, 0}, /* PyObject cname: __pyx_kp_u_isenabled */
|
||||
@@ -4341,7 +4431,6 @@ static const __Pyx_StringTabEntry __pyx_string_tab[] = {
|
||||
{__pyx_k_name, sizeof(__pyx_k_name), 0, 1, 1}, /* PyObject cname: __pyx_n_u_name */
|
||||
{__pyx_k_new, sizeof(__pyx_k_new), 0, 1, 1}, /* PyObject cname: __pyx_n_u_new */
|
||||
{__pyx_k_onnx, sizeof(__pyx_k_onnx), 0, 1, 1}, /* PyObject cname: __pyx_n_u_onnx */
|
||||
{__pyx_k_onnx_bytes, sizeof(__pyx_k_onnx_bytes), 0, 1, 1}, /* PyObject cname: __pyx_n_u_onnx_bytes */
|
||||
{__pyx_k_pickle, sizeof(__pyx_k_pickle), 0, 1, 1}, /* PyObject cname: __pyx_n_u_pickle */
|
||||
{__pyx_k_pop, sizeof(__pyx_k_pop), 0, 1, 1}, /* PyObject cname: __pyx_n_u_pop */
|
||||
{__pyx_k_pyx_PickleError, sizeof(__pyx_k_pyx_PickleError), 0, 1, 1}, /* PyObject cname: __pyx_n_u_pyx_PickleError */
|
||||
@@ -4359,6 +4448,7 @@ static const __Pyx_StringTabEntry __pyx_string_tab[] = {
|
||||
{__pyx_k_set_name, sizeof(__pyx_k_set_name), 0, 1, 1}, /* PyObject cname: __pyx_n_u_set_name */
|
||||
{__pyx_k_setstate, sizeof(__pyx_k_setstate), 0, 1, 1}, /* PyObject cname: __pyx_n_u_setstate */
|
||||
{__pyx_k_setstate_cython, sizeof(__pyx_k_setstate_cython), 0, 1, 1}, /* PyObject cname: __pyx_n_u_setstate_cython */
|
||||
{__pyx_k_source_bytes, sizeof(__pyx_k_source_bytes), 0, 1, 1}, /* PyObject cname: __pyx_n_u_source_bytes */
|
||||
{__pyx_k_state, sizeof(__pyx_k_state), 0, 1, 1}, /* PyObject cname: __pyx_n_u_state */
|
||||
{__pyx_k_staticmethod, sizeof(__pyx_k_staticmethod), 0, 1, 1}, /* PyObject cname: __pyx_n_u_staticmethod */
|
||||
{__pyx_k_stringsource, sizeof(__pyx_k_stringsource), 0, 1, 0}, /* PyObject cname: __pyx_kp_u_stringsource */
|
||||
@@ -4375,7 +4465,7 @@ static int __Pyx_InitStrings(__Pyx_StringTabEntry const *t, PyObject **target, c
|
||||
static int __Pyx_InitCachedBuiltins(__pyx_mstatetype *__pyx_mstate) {
|
||||
CYTHON_UNUSED_VAR(__pyx_mstate);
|
||||
__pyx_builtin_staticmethod = __Pyx_GetBuiltinName(__pyx_mstate->__pyx_n_u_staticmethod); if (!__pyx_builtin_staticmethod) __PYX_ERR(0, 9, __pyx_L1_error)
|
||||
__pyx_builtin_NotImplementedError = __Pyx_GetBuiltinName(__pyx_mstate->__pyx_n_u_NotImplementedError); if (!__pyx_builtin_NotImplementedError) __PYX_ERR(0, 18, __pyx_L1_error)
|
||||
__pyx_builtin_NotImplementedError = __Pyx_GetBuiltinName(__pyx_mstate->__pyx_n_u_NotImplementedError); if (!__pyx_builtin_NotImplementedError) __PYX_ERR(0, 22, __pyx_L1_error)
|
||||
return 0;
|
||||
__pyx_L1_error:;
|
||||
return -1;
|
||||
@@ -4442,24 +4532,29 @@ static int __Pyx_CreateCodeObjects(__pyx_mstatetype *__pyx_mstate) {
|
||||
__pyx_mstate_global->__pyx_codeobj_tab[0] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_engines_inference_engine_pyx, __pyx_mstate->__pyx_n_u_get_engine_filename, __pyx_k_A_q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[0])) goto bad;
|
||||
}
|
||||
{
|
||||
const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 1, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 13, 7};
|
||||
PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_onnx_bytes};
|
||||
__pyx_mstate_global->__pyx_codeobj_tab[1] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_engines_inference_engine_pyx, __pyx_mstate->__pyx_n_u_convert_from_onnx, __pyx_k_A_q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[1])) goto bad;
|
||||
const __Pyx_PyCode_New_function_description descr = {0, 0, 0, 0, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 13, 7};
|
||||
PyObject* const varnames[] = {0};
|
||||
__pyx_mstate_global->__pyx_codeobj_tab[1] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_engines_inference_engine_pyx, __pyx_mstate->__pyx_n_u_get_source_filename, __pyx_k_A_q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[1])) goto bad;
|
||||
}
|
||||
{
|
||||
const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 1, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 17, 7};
|
||||
PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_source_bytes};
|
||||
__pyx_mstate_global->__pyx_codeobj_tab[2] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_engines_inference_engine_pyx, __pyx_mstate->__pyx_n_u_convert_from_source, __pyx_k_A_q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[2])) goto bad;
|
||||
}
|
||||
{
|
||||
const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 4, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1, 87};
|
||||
PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self, __pyx_mstate->__pyx_n_u_state, __pyx_mstate->__pyx_n_u_dict_2, __pyx_mstate->__pyx_n_u_use_setstate};
|
||||
__pyx_mstate_global->__pyx_codeobj_tab[2] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_stringsource, __pyx_mstate->__pyx_n_u_reduce_cython, __pyx_k_T_G1F_a_vWA_q_q_q_0_AWKwa_0_AWK, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[2])) goto bad;
|
||||
__pyx_mstate_global->__pyx_codeobj_tab[3] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_stringsource, __pyx_mstate->__pyx_n_u_reduce_cython, __pyx_k_T_G1F_a_vWA_q_q_q_0_AWKwa_0_AWK, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[3])) goto bad;
|
||||
}
|
||||
{
|
||||
const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 2, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 16, 11};
|
||||
PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self, __pyx_mstate->__pyx_n_u_pyx_state};
|
||||
__pyx_mstate_global->__pyx_codeobj_tab[3] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_stringsource, __pyx_mstate->__pyx_n_u_setstate_cython, __pyx_k_QfA, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[3])) goto bad;
|
||||
__pyx_mstate_global->__pyx_codeobj_tab[4] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_stringsource, __pyx_mstate->__pyx_n_u_setstate_cython, __pyx_k_QfA, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[4])) goto bad;
|
||||
}
|
||||
{
|
||||
const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 5, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1, 77};
|
||||
PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_pyx_type, __pyx_mstate->__pyx_n_u_pyx_checksum, __pyx_mstate->__pyx_n_u_pyx_state, __pyx_mstate->__pyx_n_u_pyx_PickleError, __pyx_mstate->__pyx_n_u_pyx_result};
|
||||
__pyx_mstate_global->__pyx_codeobj_tab[4] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_stringsource, __pyx_mstate->__pyx_n_u_pyx_unpickle_InferenceEngine, __pyx_k_hk_A_1_uuwwx_1_7_1_2DNRS_1, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[4])) goto bad;
|
||||
__pyx_mstate_global->__pyx_codeobj_tab[5] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_stringsource, __pyx_mstate->__pyx_n_u_pyx_unpickle_InferenceEngine, __pyx_k_hk_A_1_uuwwx_1_7_1_2DNRS_1, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[5])) goto bad;
|
||||
}
|
||||
Py_DECREF(tuple_dedup_map);
|
||||
return 0;
|
||||
|
||||
@@ -11,8 +11,12 @@ cdef class InferenceEngine:
|
||||
return None
|
||||
|
||||
@staticmethod
|
||||
def convert_from_onnx(bytes onnx_bytes):
|
||||
return onnx_bytes
|
||||
def get_source_filename():
|
||||
return None
|
||||
|
||||
@staticmethod
|
||||
def convert_from_source(bytes source_bytes):
|
||||
return source_bytes
|
||||
|
||||
cdef tuple get_input_shape(self):
|
||||
raise NotImplementedError("Subclass must implement get_input_shape")
|
||||
|
||||
@@ -88,7 +88,12 @@ cdef class TensorRTEngine(InferenceEngine):
|
||||
return None
|
||||
|
||||
@staticmethod
|
||||
def convert_from_onnx(bytes onnx_model):
|
||||
def get_source_filename():
|
||||
import constants_inf
|
||||
return constants_inf.AI_ONNX_MODEL_FILE
|
||||
|
||||
@staticmethod
|
||||
def convert_from_source(bytes onnx_model):
|
||||
workspace_bytes = int(TensorRTEngine.get_gpu_memory_bytes(0) * 0.9)
|
||||
|
||||
explicit_batch_flag = 1 << int(trt.NetworkDefinitionCreationFlag.EXPLICIT_BATCH)
|
||||
|
||||
Reference in New Issue
Block a user