competition update

language_model/runtime/server/x86/python/test.py

@@ -0,0 +1,43 @@
+import os
+
+import numpy as np
+import lm_decoder
+
+decode_opts = lm_decoder.DecodeOptions(
+    7000,   # max_active
+    200,    # min_active
+    17.,    # beam 
+    8.,     # lattice_beam
+    1.0,    # acoustic_scale
+    0.98,   # ctc_blank_skip_threshold
+    10      # nbest
+)
+
+model_path = '/oak/stanford/groups/shenoy/stfan/code/nptlrig2/LanguageModelDecoder/examples/handwriting/s0/3gram_no_prune/data/lang_test'
+decode_resource = lm_decoder.DecodeResource(
+    os.path.join(model_path, 'TLG.fst'),
+    "",
+    "",
+    os.path.join(model_path, 'words.txt'),
+    ""
+)
+decoder = lm_decoder.BrainSpeechDecoder(decode_resource, decode_opts)
+
+# Load handwriting RNN logits output
+logits = np.load('test_logits.npy')
+print(logits.shape)
+
+# Rearrange logits to Kaldi character order
+# [ctc_blank, ">", ",", "?", "~", "'", a, b, ..., z]
+char_range = list(range(0, 26))
+logits = logits[:, :, [31] + [26, 27, 30, 29, 28] + char_range]
+
+# Decode
+for i in range(logits.shape[0]):
+    lm_decoder.DecodeNumpy(decoder, logits[i])
+    decoder.FinishDecoding()
+    if len(decoder.result()) > 0:
+        print(decoder.result()[0].sentence)
+    else:
+        print("No result")
+    decoder.Reset()