🤖 apply linter changes (will not trigger CI)

exo-lang · Oct 13, 2024 · fa92b6f · fa92b6f
1 parent b6296c5
commit fa92b6f
Show file tree

Hide file tree

Showing 4 changed files with 238 additions and 174 deletions.
diff --git a/examples/rvm_conv1d/conv1Di32.h b/examples/rvm_conv1d/conv1Di32.h
@@ -1,16 +1,58 @@
-#ifndef _CONV1Di32 
-#define _CONV1Di32 
+#ifndef _CONV1Di32
+#define _CONV1Di32
 // This file is automatically generated
-int32_t __attribute__((section(".xheep_data_interleaved"))) DATA[] = {
-	0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15};
+int32_t __attribute__((section(".xheep_data_interleaved")))
+DATA[] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 0, 1, 2, 3, 4,
+    5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
+    12, 13, 14, 15, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15};
 
-int32_t __attribute__((section(".xheep_data_interleaved"))) KERNELS[] = {
-	0,1,2,3,10,11,12,13,20,21,22,23,30,31,32,33,100,101,102,103,110,111,112,113,120,121,122,123,130,131,132,133,200,201,202,203,210,211,212,213,220,221,222,223,230,231,232,233,300,301,302,303,310,311,312,313,320,321,322,323,330,331,332,333,400,401,402,403,410,411,412,413,420,421,422,423,430,431,432,433,500,501,502,503,510,511,512,513,520,521,522,523,530,531,532,533,600,601,602,603,610,611,612,613,620,621,622,623,630,631,632,633,700,701,702,703,710,711,712,713,720,721,722,723,730,731,732,733,
-	800,801,802,803,810,811,812,813,820,821,822,823,830,831,832,833,900,901,902,903,910,911,912,913,920,921,922,923,930,931,932,933,1000,1001,1002,1003,1010,1011,1012,1013,1020,1021,1022,1023,1030,1031,1032,1033,1100,1101,1102,1103,1110,1111,1112,1113,1120,1121,1122,1123,1130,1131,1132,1133,1200,1201,1202,1203,1210,1211,1212,1213,1220,1221,1222,1223,1230,1231,1232,1233,1300,1301,1302,1303,1310,1311,1312,1313,1320,1321,1322,1323,1330,1331,1332,1333,1400,1401,1402,1403,1410,1411,1412,1413,1420,1421,1422,1423,1430,1431,1432,1433,1500,1501,1502,1503,1510,1511,1512,1513,1520,1521,1522,1523,1530,1531,1532,1533};
+int32_t __attribute__((section(".xheep_data_interleaved")))
+KERNELS[] = {0, 1, 2, 3, 10, 11, 12, 13, 20, 21, 22, 23, 30, 31, 32, 33, 100,
+    101, 102, 103, 110, 111, 112, 113, 120, 121, 122, 123, 130, 131, 132, 133,
+    200, 201, 202, 203, 210, 211, 212, 213, 220, 221, 222, 223, 230, 231, 232,
+    233, 300, 301, 302, 303, 310, 311, 312, 313, 320, 321, 322, 323, 330, 331,
+    332, 333, 400, 401, 402, 403, 410, 411, 412, 413, 420, 421, 422, 423, 430,
+    431, 432, 433, 500, 501, 502, 503, 510, 511, 512, 513, 520, 521, 522, 523,
+    530, 531, 532, 533, 600, 601, 602, 603, 610, 611, 612, 613, 620, 621, 622,
+    623, 630, 631, 632, 633, 700, 701, 702, 703, 710, 711, 712, 713, 720, 721,
+    722, 723, 730, 731, 732, 733, 800, 801, 802, 803, 810, 811, 812, 813, 820,
+    821, 822, 823, 830, 831, 832, 833, 900, 901, 902, 903, 910, 911, 912, 913,
+    920, 921, 922, 923, 930, 931, 932, 933, 1000, 1001, 1002, 1003, 1010, 1011,
+    1012, 1013, 1020, 1021, 1022, 1023, 1030, 1031, 1032, 1033, 1100, 1101,
+    1102, 1103, 1110, 1111, 1112, 1113, 1120, 1121, 1122, 1123, 1130, 1131,
+    1132, 1133, 1200, 1201, 1202, 1203, 1210, 1211, 1212, 1213, 1220, 1221,
+    1222, 1223, 1230, 1231, 1232, 1233, 1300, 1301, 1302, 1303, 1310, 1311,
+    1312, 1313, 1320, 1321, 1322, 1323, 1330, 1331, 1332, 1333, 1400, 1401,
+    1402, 1403, 1410, 1411, 1412, 1413, 1420, 1421, 1422, 1423, 1430, 1431,
+    1432, 1433, 1500, 1501, 1502, 1503, 1510, 1511, 1512, 1513, 1520, 1521,
+    1522, 1523, 1530, 1531, 1532, 1533};
 
-int32_t __attribute__((section(".xheep_data_interleaved"))) EXPECTED[] = {
-	416,680,944,1208,1472,1736,2000,2264,2528,2792,3056,3320,3584,2696,1800,900,2816,4680,6544,8408,10272,12136,14000,15864,17728,19592,21456,23320,25184,19496,13400,6900,5216,8680,12144,15608,19072,22536,26000,29464,32928,36392,39856,43320,46784,36296,25000,12900,7616,12680,17744,22808,27872,32936,38000,43064,48128,53192,58256,63320,68384,53096,36600,18900,10016,16680,23344,30008,36672,43336,50000,56664,63328,69992,76656,83320,89984,69896,48200,24900,12416,20680,28944,37208,45472,53736,62000,70264,78528,86792,95056,103320,111584,86696,59800,30900,14816,24680,34544,44408,54272,64136,74000,83864,93728,103592,113456,123320,133184,103496,71400,36900,17216,28680,40144,51608,63072,74536,86000,97464,108928,120392,131856,143320,154784,120296,83000,42900,
-	19616,32680,45744,58808,71872,84936,98000,111064,124128,137192,150256,163320,176384,137096,94600,48900,22016,36680,51344,66008,80672,95336,110000,124664,139328,153992,168656,183320,197984,153896,106200,54900,24416,40680,56944,73208,89472,105736,122000,138264,154528,170792,187056,203320,219584,170696,117800,60900,26816,44680,62544,80408,98272,116136,134000,151864,169728,187592,205456,223320,241184,187496,129400,66900,29216,48680,68144,87608,107072,126536,146000,165464,184928,204392,223856,243320,262784,204296,141000,72900,31616,52680,73744,94808,115872,136936,158000,179064,200128,221192,242256,263320,284384,221096,152600,78900,34016,56680,79344,102008,124672,147336,170000,192664,215328,237992,260656,283320,305984,237896,164200,84900,36416,60680,84944,109208,133472,157736,182000,206264,230528,254792,279056,303320,327584,254696,175800,90900};
+int32_t __attribute__((section(".xheep_data_interleaved"))) EXPECTED[] = {416,
+    680, 944, 1208, 1472, 1736, 2000, 2264, 2528, 2792, 3056, 3320, 3584, 2696,
+    1800, 900, 2816, 4680, 6544, 8408, 10272, 12136, 14000, 15864, 17728, 19592,
+    21456, 23320, 25184, 19496, 13400, 6900, 5216, 8680, 12144, 15608, 19072,
+    22536, 26000, 29464, 32928, 36392, 39856, 43320, 46784, 36296, 25000, 12900,
+    7616, 12680, 17744, 22808, 27872, 32936, 38000, 43064, 48128, 53192, 58256,
+    63320, 68384, 53096, 36600, 18900, 10016, 16680, 23344, 30008, 36672, 43336,
+    50000, 56664, 63328, 69992, 76656, 83320, 89984, 69896, 48200, 24900, 12416,
+    20680, 28944, 37208, 45472, 53736, 62000, 70264, 78528, 86792, 95056,
+    103320, 111584, 86696, 59800, 30900, 14816, 24680, 34544, 44408, 54272,
+    64136, 74000, 83864, 93728, 103592, 113456, 123320, 133184, 103496, 71400,
+    36900, 17216, 28680, 40144, 51608, 63072, 74536, 86000, 97464, 108928,
+    120392, 131856, 143320, 154784, 120296, 83000, 42900, 19616, 32680, 45744,
+    58808, 71872, 84936, 98000, 111064, 124128, 137192, 150256, 163320, 176384,
+    137096, 94600, 48900, 22016, 36680, 51344, 66008, 80672, 95336, 110000,
+    124664, 139328, 153992, 168656, 183320, 197984, 153896, 106200, 54900,
+    24416, 40680, 56944, 73208, 89472, 105736, 122000, 138264, 154528, 170792,
+    187056, 203320, 219584, 170696, 117800, 60900, 26816, 44680, 62544, 80408,
+    98272, 116136, 134000, 151864, 169728, 187592, 205456, 223320, 241184,
+    187496, 129400, 66900, 29216, 48680, 68144, 87608, 107072, 126536, 146000,
+    165464, 184928, 204392, 223856, 243320, 262784, 204296, 141000, 72900,
+    31616, 52680, 73744, 94808, 115872, 136936, 158000, 179064, 200128, 221192,
+    242256, 263320, 284384, 221096, 152600, 78900, 34016, 56680, 79344, 102008,
+    124672, 147336, 170000, 192664, 215328, 237992, 260656, 283320, 305984,
+    237896, 164200, 84900, 36416, 60680, 84944, 109208, 133472, 157736, 182000,
+    206264, 230528, 254792, 279056, 303320, 327584, 254696, 175800, 90900};
 
 #define N 16
 #define IC 4

diff --git a/examples/rvm_conv1d/exo/conv1d.py b/examples/rvm_conv1d/exo/conv1d.py
@@ -18,6 +18,8 @@
 W = 4
 OC = 16
 TILE = 4
+
+
 def gen_conv1d():
     @proc
     def generic_conv1d(
@@ -38,12 +40,15 @@ def generic_conv1d(
                         else:
                             y = 0
                         out[i, j] += kernels[i, c, r] * y
+
     return generic_conv1d
 
+
 ##############
 # HW LIBRARY #
 ##############
 
+
 class RVM_TILE(StaticMemory):
     NUM_RVM_TILES = 8
     StaticMemory.init_state(NUM_RVM_TILES)
@@ -125,10 +130,12 @@ def rvm_mmasa(
             for k in seq(0, 4):
                 md[i, j] += ms2[i, k] * ms1[j, k]
 
+
 ##########################
 # CUSTOM REWRITING RULES #
 ##########################
 
+
 def fuse_two_loops(p, c):
     """
     for i in ...:         <- c
@@ -186,6 +193,7 @@ def fuse_all_loops(p, cursor):
 
     return p
 
+
 def autolift_alloc(p, alloc_c, dep_set=None, max_size=0, lift=True):
     """
     for i in seq(0, 10):
@@ -219,6 +227,7 @@ def autolift_alloc(p, alloc_c, dep_set=None, max_size=0, lift=True):
             break
     return p
 
+
 def reorder_top(p, c):
     """
     for i in seq(0, 10):
@@ -317,10 +326,12 @@ def remove_redundant_loops(p, c, num=0):
             continue
     return p
 
+
 ##############
 # SCHEDULING #
 ##############
 
+
 def optimize_conv(p):
     p = rename(p, "exo_conv1d_tile_lt_kw")
 
@@ -341,7 +352,7 @@ def optimize_conv(p):
     p, (out_alloc, out_tile, body, _) = auto_stage_mem(
         p, p.find_loop("c").expand(1, 0), "out", "out_tile", rc=True
     )
-    p = autolift_alloc(p, out_tile, max_size=4 * 4 * 4, dep_set=["ioi","ii","ji"])
+    p = autolift_alloc(p, out_tile, max_size=4 * 4 * 4, dep_set=["ioi", "ii", "ji"])
 
     # Block the zero initialization and store blocks
     p = fission_as_much_as_possible(p, body)
@@ -351,13 +362,13 @@ def optimize_conv(p):
     p = lift_scope_n(p, c_loop, 3)
 
     # Stage y
-    p = autolift_alloc(p, y_alloc, max_size=4 * 4, dep_set=["r","ji"])
+    p = autolift_alloc(p, y_alloc, max_size=4 * 4, dep_set=["r", "ji"])
     p = lift_alloc(p, y_alloc, n_lifts=2)
 
     # Fission the initialization loop and remove redundant loops
     p = fission_as_much_as_possible(p, y_assign.parent())
     p = remove_redundant_loops(p, y_assign.parent(), num=2)
-    
+
     # Stage kernels to kernel_tile and y to data_tile
     ii_loop = p.forward(c_loop).body()[2].body()[0]
     p, (kernel_alloc, _, _, _) = auto_stage_mem(
@@ -386,7 +397,7 @@ def optimize_conv(p):
     p = unroll_buffer(p, kernel_alloc, 0)
     p = reuse_buffer(p, "kernel_tile_0: _", "kernel_tile_3: _")
     p = unroll_buffer(p, "out_tile", 0)
-    
+
     return p
 
 
@@ -396,4 +407,4 @@ def make_routine():
     return rvm_optimized
 
 
-exo_conv1d_tile_lt_kw = make_routine()
+exo_conv1d_tile_lt_kw = make_routine()
diff --git a/examples/rvm_conv1d/gen_stimuli.py b/examples/rvm_conv1d/gen_stimuli.py
@@ -13,25 +13,26 @@
 # CONDITIONS OF ANY KIND, either express or implied. See the License for the
 # specific language governing permissions and limitations under the License.
 
+
 def write_arr(f, name, arr, ctype, size, linebreak):
     f.write(ctype + " " + name + "[] = {\n\t")
     i = 1
     for v in arr:
         if i % size == 0:
-            f.write('%d};\n\n' % (v))
+            f.write("%d};\n\n" % (v))
         elif i % linebreak == 0:
-            f.write('%d,\n\t' % (v))
+            f.write("%d,\n\t" % (v))
         else:
-            f.write('%d,' % (v))
-        i+=1
+            f.write("%d," % (v))
+        i += 1
     return
 
 
 ################################################################################
-f = open('conv1Di32.h', 'w')
-f.write('#ifndef _CONV1Di32 \n')
-f.write('#define _CONV1Di32 \n')
-f.write('// This file is automatically generated\n')
+f = open("conv1Di32.h", "w")
+f.write("#ifndef _CONV1Di32 \n")
+f.write("#define _CONV1Di32 \n")
+f.write("// This file is automatically generated\n")
 
 
 N = 16
@@ -40,48 +41,69 @@ def write_arr(f, name, arr, ctype, size, linebreak):
 W = 4
 RANGE = 4095
 
-data   = []
-kernel  = []
+data = []
+kernel = []
 expected = []
 
 pad = 1
 
 # N C W format
-for i in range(0,IC):
-    for j in range(0,N):
+for i in range(0, IC):
+    for j in range(0, N):
         data.append(j)
-        #data.append(random.randint(-RANGE, RANGE-1))
+        # data.append(random.randint(-RANGE, RANGE-1))
 
 # O I W format
-for i in range(0,OC):
-    for j in range(0,IC):
-        for k in range(0,W):
-            kernel.append(i*100+j*10+k)
-            #kernel.append(random.randint(-RANGE, RANGE-1))
+for i in range(0, OC):
+    for j in range(0, IC):
+        for k in range(0, W):
+            kernel.append(i * 100 + j * 10 + k)
+            # kernel.append(random.randint(-RANGE, RANGE-1))
 
 # O W format
-for i in range(0,OC):
-    for j in range(0,N):
+for i in range(0, OC):
+    for j in range(0, N):
         sum = 0
-        for w_i in range(0,W):
-            for w_j in range(0,IC):
+        for w_i in range(0, W):
+            for w_j in range(0, IC):
                 data_idx = j + w_i
                 data_at_idx = 0
                 if data_idx < N:
                     data_at_idx = data[w_j * N + j + w_i]
-                sum += kernel[(IC * i + w_j)*W + w_i] * data_at_idx
+                sum += kernel[(IC * i + w_j) * W + w_i] * data_at_idx
         expected.append(sum)
 
 
-write_arr(f, 'DATA'  ,   data, 'int32_t __attribute__((section(".xheep_data_interleaved")))', IC * N, 128)
-write_arr(f, 'KERNELS' ,   kernel, 'int32_t __attribute__((section(".xheep_data_interleaved")))', OC * IC * W, 128)
-write_arr(f, 'EXPECTED', expected, 'int32_t __attribute__((section(".xheep_data_interleaved")))', OC * N, 128)
-
-f.write('#define N %d\n' % N)
-f.write('#define IC %d\n' % IC)
-f.write('#define W %d\n' % W)
-f.write('#define OC %d\n' % OC)
-f.write('#define PAD %d\n' % 1)
-
-
-f.write('#endif')
+write_arr(
+    f,
+    "DATA",
+    data,
+    'int32_t __attribute__((section(".xheep_data_interleaved")))',
+    IC * N,
+    128,
+)
+write_arr(
+    f,
+    "KERNELS",
+    kernel,
+    'int32_t __attribute__((section(".xheep_data_interleaved")))',
+    OC * IC * W,
+    128,
+)
+write_arr(
+    f,
+    "EXPECTED",
+    expected,
+    'int32_t __attribute__((section(".xheep_data_interleaved")))',
+    OC * N,
+    128,
+)
+
+f.write("#define N %d\n" % N)
+f.write("#define IC %d\n" % IC)
+f.write("#define W %d\n" % W)
+f.write("#define OC %d\n" % OC)
+f.write("#define PAD %d\n" % 1)
+
+
+f.write("#endif")