trying to test softmax_ce_t

1 files changed, 45 insertions, 0 deletions

diff --git a/nerv/examples/lmptb/rnn/init.lua b/nerv/examples/lmptb/rnn/init.lua
new file mode 100644
index 0000000..0e08cb6
--- /dev/null
+++ b/nerv/examples/lmptb/rnn/init.lua
@@ -0,0 +1,45 @@
+local Layer = nerv.class('nerv.LayerT')
+
+function Layer:__init(id, global_conf, layer_conf)
+    nerv.error_method_not_implemented()
+end
+
+function Layer:init(batch_size, chunk_size)
+    nerv.error_method_not_implemented()
+end
+
+function Layer:update(bp_err, input, output, t)
+    nerv.error_method_not_implemented()
+end
+
+function Layer:propagate(input, output, t)
+    nerv.error_method_not_implemented()
+end
+
+function Layer:back_propagate(bp_err, next_bp_err, input, output, t)
+    nerv.error_method_not_implemented()
+end
+
+function Layer:check_dim_len(len_in, len_out)
+    local expected_in = #self.dim_in
+    local expected_out = #self.dim_out
+    if len_in > 0 and expected_in ~= len_in then
+        nerv.error("layer %s expects %d inputs, %d given",
+                    self.id, len_in, expected_in)
+    end
+    if len_out > 0 and expected_out ~= len_out then
+        nerv.error("layer %s expects %d outputs, %d given",
+                    self.id, len_out, expected_out)
+    end
+end
+
+function Layer:get_params()
+    nerv.error_method_not_implemented()
+end
+
+function Layer:get_dim()
+    return self.dim_in, self.dim_out
+end
+
+nerv.include('tnn.lua')
+nerv.include('softmax_ce_t.lua')