Fix test

Author: lantiga

src/backends/tensorflow.c

@@ -39,6 +39,7 @@ typedef struct TFDLManagedTensorCtx TFDLManagedTensorCtx;
 
 TFDLManagedTensorCtx *TFDLManagedTensorCtx_Create(TFE_TensorHandle *h, TF_Status *status) {
     TFDLManagedTensorCtx *ctx = RedisModule_Alloc(sizeof(TFDLManagedTensorCtx));
+    ctx->reference = h;
     ctx->ndim = TFE_TensorHandleNumDims(h, status);
     ctx->shape = RedisModule_Calloc(ctx->ndim, sizeof(int64_t));
     ctx->strides = RedisModule_Calloc(ctx->ndim, sizeof(int64_t));
@@ -257,15 +258,9 @@ void *TFE_HandleToDLPack(TFE_TensorHandle *h, TF_Status *status) {
     dlm_tensor->dl_tensor.data = tf_dlm_data;
     dlm_tensor->dl_tensor.dtype = tf_dlm_type;
     dlm_tensor->dl_tensor.shape = tf_dlm_tensor_ctx->shape;
-    // There are two ways to represent compact row-major data
-    // 1) nullptr indicates tensor is compact and row-majored.
-    // 2) fill in the strides array as the real case for compact row-major data.
-    // Here we choose option 2, since some frameworks didn't handle the strides
-    // argument properly.
     dlm_tensor->dl_tensor.strides = tf_dlm_tensor_ctx->strides;
-
-    // TF doesn't handle the strides and byte_offsets here
     dlm_tensor->dl_tensor.byte_offset = 0;
+
     return (void *)dlm_tensor;
 }
 

tests/flow/tests_dag.py

@@ -818,11 +818,8 @@ def test_dag_modelrun_financialNet_no_writes(env):
                               'INPUTS', 'transaction', 'reference', 'OUTPUTS', 'output', 'BLOB', model_pb)
     env.assertEqual(ret, b'OK')
 
-    MAX_TRANSACTIONS = 2
-
     for tensor_number in range(1, MAX_TRANSACTIONS):
-        # for repetition in range(1, 10):
-        for repetition in range(1, 2):
+        for repetition in range(1, 10):
             reference_tensor = creditcard_referencedata[tensor_number]
             transaction_tensor = creditcard_transactions[tensor_number]
             result_tensor_keyname = 'resultTensor{{hhh}}{}'.format(tensor_number)
@@ -836,9 +833,6 @@ def test_dag_modelrun_financialNet_no_writes(env):
             ret = con.execute_command("EXISTS {}".format(reference_tensor_keyname))
             env.assertEqual(ret, 1)
 
-            # print(reference_tensor)
-            print(transaction_tensor)
-
             ret = con.execute_command(
                 'AI.DAGRUN', 'LOAD', '1', reference_tensor_keyname, '|>',
                 'AI.TENSORSET', transaction_tensor_keyname, 'FLOAT', 1, 30,'BLOB', transaction_tensor.tobytes(), '|>',