Decreased amount of RAM used by Sample Generator.

core/mplib/MPSharedList.py

@@ -0,0 +1,146 @@
+import multiprocessing
+import pickle
+import struct
+from core.joblib import Subprocessor
+
+class MPSharedList():
+    """
+    Provides read-only pickled list of constant objects via shared memory aka 'multiprocessing.Array'
+    Thus no 4GB limit for subprocesses.
+    
+    supports list concat via + or sum()
+    """
+    
+    def __init__(self, obj_list):     
+        if obj_list is None:
+            self.obj_counts    = None
+            self.table_offsets = None
+            self.data_offsets  = None
+            self.sh_bs         = None
+        else:   
+            obj_count, table_offset, data_offset, sh_b = MPSharedList.bake_data(obj_list)
+
+            self.obj_counts    = [obj_count]
+            self.table_offsets = [table_offset]
+            self.data_offsets  = [data_offset]
+            self.sh_bs         = [sh_b]
+        
+    def __add__(self, o):
+        if isinstance(o, MPSharedList):
+            m = MPSharedList(None)
+            m.obj_counts    = self.obj_counts    + o.obj_counts   
+            m.table_offsets = self.table_offsets + o.table_offsets
+            m.data_offsets  = self.data_offsets  + o.data_offsets 
+            m.sh_bs         = self.sh_bs         + o.sh_bs        
+            return m
+        elif isinstance(o, int):
+            return self
+        else:
+            raise ValueError(f"MPSharedList object of class {o.__class__} is not supported for __add__ operator.")
+    
+    def __radd__(self, o):
+        return self+o
+        
+    def __len__(self):
+        return sum(self.obj_counts)
+         
+    def __getitem__(self, key):    
+        obj_count = sum(self.obj_counts)
+        if key < 0:
+            key = obj_count+key
+        if key < 0 or key >= obj_count:
+            raise ValueError("out of range")
+        
+        for i in range(len(self.obj_counts)):
+            
+            if key < self.obj_counts[i]:
+                table_offset = self.table_offsets[i]
+                data_offset = self.data_offsets[i]
+                sh_b = self.sh_bs[i]
+                break
+            key -= self.obj_counts[i]
+
+        offset_start, offset_end = struct.unpack('<QQ', bytes(sh_b[ table_offset + key*8     : table_offset + (key+2)*8]) )
+
+        return pickle.loads( bytes(sh_b[ data_offset + offset_start : data_offset + offset_end ]) )
+    
+    def __iter__(self):
+        for i in range(self.__len__()):
+            yield self.__getitem__(i)
+            
+    @staticmethod
+    def bake_data(obj_list):
+        if not isinstance(obj_list, list):
+            raise ValueError("MPSharedList: obj_list should be list type.")
+        
+        obj_count = len(obj_list)
+        
+        if obj_count != 0:            
+            obj_pickled_ar = [pickle.dumps(o, 4) for o in obj_list]
+            
+            table_offset = 0
+            table_size   = (obj_count+1)*8
+            data_offset  = table_offset + table_size
+            data_size    = sum([len(x) for x in obj_pickled_ar])        
+            
+            sh_b = multiprocessing.RawArray('B', table_size + data_size)        
+            sh_b[0:8] = struct.pack('<Q', obj_count)  
+            
+            offset = 0
+
+            sh_b_table = bytes()
+            offsets = []
+            
+            offset = 0
+            for i in range(obj_count):
+                offsets.append(offset)
+                offset += len(obj_pickled_ar[i])
+            offsets.append(offset)
+    
+            sh_b[table_offset:table_offset+table_size] = struct.pack( '<'+'Q'*len(offsets), *offsets )
+
+            ArrayFillerSubprocessor(sh_b, [ (data_offset+offsets[i], obj_pickled_ar[i] ) for i in range(obj_count) ] ).run()
+           
+        return obj_count, table_offset, data_offset, sh_b
+        
+        
+
+class ArrayFillerSubprocessor(Subprocessor):
+    """
+    Much faster to fill shared memory via subprocesses rather than direct whole bytes fill.
+    """
+    #override
+    def __init__(self, sh_b, data_list ):
+        self.sh_b = sh_b        
+        self.data_list = data_list
+        super().__init__('ArrayFillerSubprocessor', ArrayFillerSubprocessor.Cli, 60)
+
+    #override
+    def process_info_generator(self):
+        for i in range(multiprocessing.cpu_count()):
+            yield 'CPU%d' % (i), {}, {'sh_b':self.sh_b}
+
+    #override
+    def get_data(self, host_dict):
+        if len(self.data_list) > 0:
+            return self.data_list.pop(0)
+
+        return None
+
+    #override
+    def on_data_return (self, host_dict, data):
+        self.data_list.insert(0, data)
+
+    #override
+    def on_result (self, host_dict, data, result):
+        pass
+
+    class Cli(Subprocessor.Cli):
+        #overridable optional
+        def on_initialize(self, client_dict):
+            self.sh_b = client_dict['sh_b']
+            
+        def process_data(self, data):
+            offset, b = data
+            self.sh_b[offset:offset+len(b)]=b
+            return 0

core/mplib/__init__.py

@@ -1,3 +1,4 @@
+from .MPSharedList import MPSharedList
 import multiprocessing
 import threading
 import time

samplelib/SampleGeneratorFace.py

@@ -1,5 +1,4 @@
 import multiprocessing
-import pickle
 import time
 import traceback
 
@@ -12,7 +11,6 @@ from facelib import LandmarksProcessor
 from samplelib import (SampleGeneratorBase, SampleLoader, SampleProcessor,
                        SampleType)
 
-
 '''
 arg
 output_sample_types = [
@@ -59,13 +57,10 @@ class SampleGeneratorFace(SampleGeneratorBase):
             ct_samples = None
             ct_index_host = None
 
-        pickled_samples = pickle.dumps(samples, 4)
-        ct_pickled_samples = pickle.dumps(ct_samples, 4) if ct_samples is not None else None
-
         if self.debug:
-            self.generators = [ThisThreadGenerator ( self.batch_func, (pickled_samples, index_host.create_cli(), ct_pickled_samples, ct_index_host.create_cli() if ct_index_host is not None else None) )]
+            self.generators = [ThisThreadGenerator ( self.batch_func, (samples, index_host.create_cli(), ct_samples, ct_index_host.create_cli() if ct_index_host is not None else None) )]
         else:
-            self.generators = [SubprocessGenerator ( self.batch_func, (pickled_samples, index_host.create_cli(), ct_pickled_samples, ct_index_host.create_cli() if ct_index_host is not None else None), start_now=False ) \
+            self.generators = [SubprocessGenerator ( self.batch_func, (samples, index_host.create_cli(), ct_samples, ct_index_host.create_cli() if ct_index_host is not None else None), start_now=False ) \
                                for i in range(self.generators_count) ]
                                
             SubprocessGenerator.start_in_parallel( self.generators )
@@ -90,11 +85,8 @@ class SampleGeneratorFace(SampleGeneratorBase):
         return next(generator)
 
     def batch_func(self, param ):
-        pickled_samples, index_host, ct_pickled_samples, ct_index_host = param
+        samples, index_host, ct_samples, ct_index_host = param
-        
+ 
-        samples = pickle.loads(pickled_samples)
-        ct_samples = pickle.loads(ct_pickled_samples) if ct_pickled_samples is not None else None
-
         bs = self.batch_size
         while True:
             batches = None

samplelib/SampleGeneratorFaceXSeg.py

@@ -11,7 +11,7 @@ from core import imagelib, mplib, pathex
 from core.imagelib import sd
 from core.cv2ex import *
 from core.interact import interact as io
-from core.joblib import SubprocessGenerator, ThisThreadGenerator
+from core.joblib import Subprocessor, SubprocessGenerator, ThisThreadGenerator
 from facelib import LandmarksProcessor
 from samplelib import (SampleGeneratorBase, SampleLoader, SampleProcessor, SampleType)
 
@@ -23,28 +23,24 @@ class SampleGeneratorFaceXSeg(SampleGeneratorBase):
         super().__init__(debug, batch_size)
         self.initialized = False
 
-        samples = []
+        samples = sum([ SampleLoader.load (SampleType.FACE, path) for path in paths ]  )
-        for path in paths:
+        seg_sample_idxs = SegmentedSampleFilterSubprocessor(samples).run()
-            samples += SampleLoader.load (SampleType.FACE, path)
+        
-
+        seg_samples_len = len(seg_sample_idxs)
-        seg_samples = [ sample for sample in samples if sample.seg_ie_polys.get_pts_count() != 0]
-        seg_samples_len = len(seg_samples)
         if seg_samples_len == 0:
             raise Exception(f"No segmented faces found.")
         else:
             io.log_info(f"Using {seg_samples_len} segmented samples.")
-            
+
-        pickled_samples = pickle.dumps(seg_samples, 4)
-        
         if self.debug:
             self.generators_count = 1
         else:
             self.generators_count = max(1, generators_count)
 
         if self.debug:
-            self.generators = [ThisThreadGenerator ( self.batch_func, (pickled_samples, resolution, face_type, data_format) )]
+            self.generators = [ThisThreadGenerator ( self.batch_func, (samples, seg_sample_idxs, resolution, face_type, data_format) )]
         else:
-            self.generators = [SubprocessGenerator ( self.batch_func, (pickled_samples, resolution, face_type, data_format), start_now=False ) \
+            self.generators = [SubprocessGenerator ( self.batch_func, (samples, seg_sample_idxs, resolution, face_type, data_format), start_now=False ) \
                                for i in range(self.generators_count) ]
 
             SubprocessGenerator.start_in_parallel( self.generators )
@@ -66,12 +62,9 @@ class SampleGeneratorFaceXSeg(SampleGeneratorBase):
         return next(generator)
 
     def batch_func(self, param ):
-        pickled_samples, resolution, face_type, data_format = param
+        samples, seg_sample_idxs, resolution, face_type, data_format = param
-
+   
-        samples = pickle.loads(pickled_samples)    
-            
         shuffle_idxs = []
-        idxs = [*range(len(samples))]
         
         random_flip = True
         rotation_range=[-10,10]
@@ -91,7 +84,7 @@ class SampleGeneratorFaceXSeg(SampleGeneratorBase):
             while n_batch < bs:
                 try:
                     if len(shuffle_idxs) == 0:
-                        shuffle_idxs = idxs.copy()
+                        shuffle_idxs = seg_sample_idxs.copy()
                         np.random.shuffle(shuffle_idxs)
                     idx = shuffle_idxs.pop()
                     
@@ -146,3 +139,56 @@ class SampleGeneratorFaceXSeg(SampleGeneratorBase):
                     io.log_err ( traceback.format_exc() )
 
             yield [ np.array(batch) for batch in batches]
+
+
+
+class SegmentedSampleFilterSubprocessor(Subprocessor):
+    #override
+    def __init__(self, samples ):
+        self.samples = samples        
+        self.samples_len = len(self.samples)
+
+        self.idxs = [*range(self.samples_len)]
+        self.result = []
+        super().__init__('SegmentedSampleFilterSubprocessor', SegmentedSampleFilterSubprocessor.Cli, 60)
+
+    #override
+    def process_info_generator(self):
+        for i in range(multiprocessing.cpu_count()):
+            yield 'CPU%d' % (i), {}, {'samples':self.samples}
+
+    #override
+    def on_clients_initialized(self):
+        io.progress_bar ("Filtering", self.samples_len)
+
+    #override
+    def on_clients_finalized(self):
+        io.progress_bar_close()
+        
+    #override
+    def get_data(self, host_dict):
+        if len (self.idxs) > 0:
+            return self.idxs.pop(0)
+
+        return None
+
+    #override
+    def on_data_return (self, host_dict, data):
+        self.idxs.insert(0, data)
+
+    #override
+    def on_result (self, host_dict, data, result):
+        idx, is_ok = result
+        if is_ok:
+            self.result.append(idx)
+        io.progress_bar_inc(1)
+    def get_result(self):
+        return self.result
+        
+    class Cli(Subprocessor.Cli):
+        #overridable optional
+        def on_initialize(self, client_dict):
+            self.samples = client_dict['samples']
+            
+        def process_data(self, idx):
+            return idx, self.samples[idx].seg_ie_polys.get_pts_count() != 0

samplelib/SampleLoader.py

@@ -6,6 +6,7 @@ from pathlib import Path
 
 import samplelib.PackedFaceset
 from core import pathex
+from core.mplib import MPSharedList
 from core.interact import interact as io
 from core.joblib import Subprocessor
 from DFLIMG import *
@@ -33,6 +34,9 @@ class SampleLoader:
 
     @staticmethod
     def load(sample_type, samples_path, subdirs=False):
+        """
+        Return MPSharedList of samples
+        """
         samples_cache = SampleLoader.samples_cache
 
         if str(samples_path) not in samples_cache.keys():
@@ -56,12 +60,12 @@ class SampleLoader:
 
                 if result is None:
                     result = SampleLoader.load_face_samples( pathex.get_image_paths(samples_path, subdirs=subdirs) )
-                samples[sample_type] = result
 
+                samples[sample_type] = MPSharedList(result)
         elif          sample_type == SampleType.FACE_TEMPORAL_SORTED:
                 result = SampleLoader.load (SampleType.FACE, samples_path)
                 result = SampleLoader.upgradeToFaceTemporalSortedSamples(result)
-                samples[sample_type] = result
+                samples[sample_type] = MPSharedList(result)
 
         return samples[sample_type]