[context33] - increase momentum 0.5→0.7; run outputs 99% recon, 88% next-step
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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@@ -11,8 +11,8 @@
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"shell.execute_reply": "2026-05-31T13:42:50.945911Z"
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"ExecuteTime": {
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}
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},
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"source": [
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@@ -32,7 +32,7 @@
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"from rbm.status import CheckpointStatus"
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],
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"outputs": [],
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"execution_count": 27
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"execution_count": 47
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},
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{
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"cell_type": "code",
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@@ -45,8 +45,8 @@
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"shell.execute_reply": "2026-05-31T13:42:50.952461Z"
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},
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"ExecuteTime": {
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"start_time": "2026-05-31T18:01:00.463411358Z"
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"end_time": "2026-05-31T18:06:04.880711653Z",
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"start_time": "2026-05-31T18:06:04.841414824Z"
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}
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"source": [
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@@ -54,7 +54,7 @@
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"SENSORY_SIZE = 40 # numVisibleX * numVisibleY = 1 * 40\n",
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"CONTEXT_SIZE = 256 # numContext = numHidden\n",
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"LEARNING_RATE = 0.05 # learningRate\n",
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"MOMENTUM = 0.5 # momentum\n",
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"MOMENTUM = 0.7 # momentum\n",
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"NUM_EPOCHS = 100 # numEpochs\n",
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"MINI_BATCH = 100 # miniBatchSize\n",
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"NUM_GIBBS = 3 # numGibbs\n",
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@@ -71,7 +71,7 @@
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"char_to_idx = {c: i for i, c in enumerate(chars)}"
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],
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"outputs": [],
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"execution_count": 28
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"execution_count": 48
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},
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{
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"cell_type": "code",
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@@ -84,8 +84,8 @@
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"shell.execute_reply": "2026-05-31T13:42:50.958632Z"
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},
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"ExecuteTime": {
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"end_time": "2026-05-31T18:01:00.570664090Z",
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"start_time": "2026-05-31T18:01:00.512242185Z"
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"end_time": "2026-05-31T18:06:04.938144862Z",
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"start_time": "2026-05-31T18:06:04.881644183Z"
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}
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},
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"source": "# ── Training sentence ──────────────────────────────────────────────────────\nSENTENCE = (\n \"Call me Ishmael. Some years ago, never mind how long precisely, \"\n \"having little money in my pocket and nothing particular to interest \"\n \"me on shore, I thought I would sail about a little.\"\n)\n\n# Convert to uppercase, keep only in-vocab characters\nSENTENCE = ''.join(c for c in SENTENCE.upper() if c in ALLOWED)\nN_SAMPLES = len(SENTENCE)\n\nsensory_np = np_cpu.zeros((N_SAMPLES, SENSORY_SIZE), dtype=np_cpu.float64)\nfor i, c in enumerate(SENTENCE):\n sensory_np[i, char_to_idx[c]] = 1.0\n\ndecoded = SENTENCE\nprint(f\"Sentence : '{decoded}'\")\nprint(f\"Length : {N_SAMPLES} chars\")",
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@@ -99,7 +99,7 @@
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]
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}
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],
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"execution_count": 29
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"execution_count": 49
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},
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{
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"cell_type": "code",
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@@ -112,8 +112,8 @@
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"shell.execute_reply": "2026-05-31T13:42:51.207444Z"
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},
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"ExecuteTime": {
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"end_time": "2026-05-31T18:01:00.981089507Z",
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"start_time": "2026-05-31T18:01:00.571331995Z"
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"end_time": "2026-05-31T18:06:05.261711758Z",
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"start_time": "2026-05-31T18:06:04.939234537Z"
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}
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},
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"source": [
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@@ -146,7 +146,7 @@
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}
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}
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],
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"execution_count": 30
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"execution_count": 50
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{
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"cell_type": "code",
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@@ -159,8 +159,8 @@
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"shell.execute_reply": "2026-05-31T13:42:51.212592Z"
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},
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"ExecuteTime": {
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"end_time": "2026-05-31T18:01:01.035739430Z",
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"start_time": "2026-05-31T18:01:00.981681957Z"
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"end_time": "2026-05-31T18:06:05.316035425Z",
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"start_time": "2026-05-31T18:06:05.262504600Z"
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}
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},
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"source": "# ── Prepare sequences for StackRnn ─────────────────────────────────────────\n# Tile the single sentence N_REPEAT times to form a real batch so GPU/CPU\n# matrix ops are (N_REPEAT, 168) instead of (1, 168).\nN_REPEAT = 500\nsequences = np_cpu.tile(sensory_np[np_cpu.newaxis, :, :], (N_REPEAT, 1, 1))\nprint(f\"sequences shape : {sequences.shape} → {N_REPEAT} × {N_SAMPLES} chars\")",
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@@ -173,7 +173,7 @@
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]
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}
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],
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"execution_count": 31
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"execution_count": 51
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},
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{
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"cell_type": "code",
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@@ -186,8 +186,8 @@
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"shell.execute_reply": "2026-05-31T13:42:51.319006Z"
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},
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"ExecuteTime": {
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"end_time": "2026-05-31T18:01:01.087502997Z",
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"start_time": "2026-05-31T18:01:01.036405964Z"
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"end_time": "2026-05-31T18:06:05.384091288Z",
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"start_time": "2026-05-31T18:06:05.327317819Z"
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}
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},
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"source": [
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@@ -234,7 +234,7 @@
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]
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}
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],
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"execution_count": 32
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"execution_count": 52
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},
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{
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"cell_type": "code",
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@@ -247,7 +247,7 @@
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"shell.execute_reply": "2026-05-31T13:44:35.696410Z"
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},
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"ExecuteTime": {
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"start_time": "2026-05-31T18:01:01.094798239Z"
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"start_time": "2026-05-31T18:06:05.385095367Z"
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}
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},
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"source": [
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@@ -304,40 +304,8 @@
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"text": [
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"-------------------------------------------\n",
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"Entity-296x256: progress : 1%\n",
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"Entity-296x256: err_rms : 0.0002205270517712705\n",
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"Entity-296x256: l2_norm : 142.99783613789947\n",
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"-------------------------------------------\n",
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"Entity-296x256: progress : 11%\n",
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"Entity-296x256: err_rms : 5.279407091985102e-06\n",
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"Entity-296x256: l2_norm : 143.43850704438344\n",
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"-------------------------------------------\n",
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"Entity-296x256: progress : 21%\n",
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"Entity-296x256: err_rms : 4.5788413842108285e-06\n",
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"Entity-296x256: l2_norm : 143.87610314823223\n",
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"-------------------------------------------\n",
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"Entity-296x256: progress : 31%\n",
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"Entity-296x256: err_rms : 4.457335070322053e-06\n",
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"Entity-296x256: l2_norm : 144.2866792344391\n",
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"-------------------------------------------\n",
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"Entity-296x256: progress : 41%\n",
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"Entity-296x256: err_rms : 4.415657584538288e-06\n",
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"Entity-296x256: l2_norm : 144.68009848927727\n",
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"-------------------------------------------\n",
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"Entity-296x256: progress : 51%\n",
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"Entity-296x256: err_rms : 4.39380821377769e-06\n",
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"Entity-296x256: l2_norm : 145.060477619678\n",
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"-------------------------------------------\n",
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"Entity-296x256: progress : 61%\n",
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"Entity-296x256: err_rms : 4.377943875271283e-06\n",
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"Entity-296x256: l2_norm : 145.43015581564566\n",
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"-------------------------------------------\n",
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"Entity-296x256: progress : 71%\n",
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"Entity-296x256: err_rms : 4.363603864787239e-06\n",
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"Entity-296x256: l2_norm : 145.79070936590585\n",
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"-------------------------------------------\n",
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"Entity-296x256: progress : 81%\n",
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"Entity-296x256: err_rms : 4.34883619751348e-06\n",
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"Entity-296x256: l2_norm : 146.14331420811664\n"
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"Entity-296x256: err_rms : 4.153017505591589e-06\n",
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"Entity-296x256: l2_norm : 149.9841498059769\n"
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]
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}
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],
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@@ -10,12 +10,12 @@ from rbm.matrix import Mat, np, convert
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from rbm.status import CheckpointStatus
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DATA_DIR = '/media/jens/cifs/bilder/MachineVision/Caltech_WebFaces/'
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PATCH = 32
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STRIDE = 16 # 50% overlap; set equal to PATCH for non-overlapping
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PATCH = 8
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STRIDE = 4 # 50% overlap; set equal to PATCH for non-overlapping
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GRAYSCALE = False # reassigned in __main__ when --grayscale is set
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N_CH = 1 if GRAYSCALE else 3
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N_VIS = N_CH * PATCH * PATCH # 1024 grayscale / 3072 colour
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N_HID = 256
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N_HID = 64
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N_IMAGES = 50
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