Contents
mdf-env
Specification
Examples
Export Formats
Functions
API Reference
evaluate_expr()
evaluate_onnx_expr()
get_required_variables_from_expression()
main()
EvaluableFunction
EvaluableFunction.evaluate()
EvaluableGraph
EvaluableGraph.evaluate()
EvaluableGraph.evaluate_edge()
EvaluableGraph.parse_condition()
EvaluableInput
EvaluableInput.set_input_value()
EvaluableInput.evaluate()
EvaluableNode
EvaluableNode.evaluate()
EvaluableNode.get_output()
EvaluableOutput
EvaluableOutput.evaluate()
EvaluableParameter
EvaluableParameter.get_current_value()
EvaluableParameter.evaluate()
convert_states_to_stateful_parameters()
change_goal()
check_termination()
chunk_to_string()
conflict_resolution_function()
match_production()
pattern_matching_function()
pattern_to_string()
retrieve_chunk()
update_buffer()
update_goal()
update_retrieval()
Buffer
Chunk
Associated
BlendingMemory
DMAssociate
DMBaseLevel
DMFixed
DMInhibition
DMNoise
DMSalience
DMSpacing
DMSpreading
Finst
Memory
MemorySubModule
Partial
file_exists()
finished()
log()
DummyLog
Log
LogProxy
Trace
log_everything()
MethodGeneratorWrapper
MethodGeneratorWrapper.__call__()
MethodWrapper
MethodWrapper.__call__()
Model
get()
parse()
partialmatch()
Pattern
PatternException
Event
Scheduler
Trigger
SchedulerError
drift_diffusion_integrator()
abs()
acos()
acosh()
add()
and()
argmax()
argmin()
asin()
asinh()
atan()
atanh()
averagepool()
batchnormalization()
bernoulli()
bitshift()
cast()
castlike()
ceil()
celu()
clip()
compress()
concat()
concatfromsequence()
constant()
constantofshape()
conv()
convert_type()
convinteger()
convtranspose()
cos()
cosh()
cumsum()
depthtospace()
dequantizelinear()
det()
div()
dropout()
dynamicquantizelinear()
einsum()
elu()
equal()
erf()
exp()
expand()
eyelike()
flatten()
floor()
gather()
gatherelements()
gathernd()
gemm()
get_all_schemas_version()
get_onnx_ops()
get_onnx_schema()
globalaveragepool()
globallppool()
globalmaxpool()
greater()
greaterorequal()
gru()
hardmax()
hardsigmoid()
hardswish()
identity()
if()
import_class()
instancenormalization()
isinf()
isnan()
leakyrelu()
less()
lessorequal()
logsoftmax()
loop()
lpnormalization()
lppool()
lrn()
lstm()
matmul()
matmulinteger()
max()
maxpool()
maxroipool()
maxunpool()
mean()
meanvariancenormalization()
min()
mod()
mul()
multinomial()
neg()
negativeloglikelihoodloss()
nonmaxsuppression()
nonzero()
not()
onehot()
optional()
optionalgetelement()
optionalhaselement()
or()
pad()
pow()
predict_with_onnxruntime()
prelu()
qlinearconv()
qlinearmatmul()
quantizelinear()
randomnormal()
randomnormallike()
randomuniform()
randomuniformlike()
range()
reciprocal()
reducel1()
reducel2()
reducelogsum()
reducelogsumexp()
reducemax()
reducemean()
reducemin()
reduceprod()
reducesum()
reducesumsquare()
relu()
reshape()
resize()
reversesequence()
rnn()
roialign()
round()
run_onnx_op()
scan()
scatter()
scatterelements()
scatternd()
selu()
sequenceat()
sequenceconstruct()
sequenceempty()
sequenceerase()
sequenceinsert()
sequencelength()
shape()
shrink()
sigmoid()
sign()
sin()
sinh()
size()
slice()
softmax()
softmaxcrossentropyloss()
softplus()
softsign()
spacetodepth()
split()
splittosequence()
sqrt()
squeeze()
stringnormalizer()
sub()
sum()
tan()
tanh()
tfidfvectorizer()
thresholdedrelu()
tile()
topk()
transpose()
trilu()
unique()
unsqueeze()
upsample()
where()
xor()
add_function_from_callable()
add_mdf_function()
add_public_functions_from_module()
create_python_expression()
create_python_function()
parse_description_and_args()
substitute_args()
actr_to_mdf()
build_model()
format_bold()
format_condition()
format_function()
format_input()
format_label()
format_num()
format_output()
format_param()
format_standard_func()
format_standard_func_long()
format_term_condition()
match_in_expr()
mdf_to_graphviz()
safe_comparitor()
convert_mdf_file_to_onnx()
generate_onnx_graph()
generate_onnx_node()
mdf_to_onnx()
convert_file()
find_subgraphs()
get_category_of_onnx_node()
get_color_for_onnx_category()
get_onnx_attribute()
get_shape_params()
id_to_port()
onnx_node_to_mdf()
onnx_to_mdf()
build_script()
func_args()
generate_main_forward()
get_module_declaration_text()
mdf_to_pytorch()
sym()
convert_to_serializable()
get_graph_constants()
make_func_id()
make_model_graph_name()
make_node_id()
process_onnx_schema()
process_torch_schema()
pytorch_to_mdf()
torchnode_to_mdfnode()
translate_graph()
PortMapper
PortMapper.id_to_port()
PortMapper.port_to_id()
parsed_structure_factory()
parsed_unstructure_factory()
v()
Condition
ConditionSet
Edge
Function
Graph
Graph.get_node()
Graph.dependency_dict
Graph.inputs
InputPort
Model.to_graph_image()
Node
Node.get_parameter()
Node.get_input_port()
Node.get_output_port()
OutputPort
Parameter
Parameter.summary()
Parameter.is_stateful()
ParameterCondition
color_rgb_to_hex()
create_example_node()
is_number()
load_mdf()
load_mdf_json()
load_mdf_yaml()
print_summary()
simple_connect()
Relu takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the rectified linear function, y = max(0, x), is applied to the tensor elementwise.